From 41bbafa48e35fddd537d8183cf7a84702199389e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?L=C3=AA=20Nguy=C3=AAn=20Hoang?= Date: Thu, 2 Jan 2025 22:21:11 +0100 Subject: [PATCH] WIP Scaling left to adapt. And then tests, tests, tests... --- solidago/src/solidago/pipeline/__init__.py | 6 +- .../solidago/pipeline/aggregation/__init__.py | 4 +- .../solidago/pipeline/aggregation/average.py | 80 +- .../aggregation/entitywise_qr_quantile.py | 149 +- solidago/src/solidago/pipeline/pipeline.py | 19 +- .../solidago/pipeline/post_process/base.py | 33 +- .../pipeline/post_process/no_post_process.py | 29 - .../solidago/pipeline/post_process/squash.py | 42 +- .../pipeline/preference_learning/base.py | 4 +- .../generalized_bradley_terry.py | 174 +- .../lbfgs_generalized_bradley_terry.py | 167 +- .../pipeline/scaling/quantile_zero_shift.py | 95 +- .../solidago/pipeline/scaling/standardize.py | 24 +- .../pipeline/trust_propagation/base.py | 2 +- .../solidago/pipeline/voting_rights/base.py | 2 +- .../primitives/datastructure/nested_dict.py | 11 + solidago/src/solidago/primitives/optimize.py | 6 +- .../src/solidago/state/assessments/base.py | 18 +- .../src/solidago/state/comparisons/base.py | 25 +- solidago/src/solidago/state/models/base.py | 12 +- solidago/src/solidago/state/models/direct.py | 3 + .../solidago/state/models/post_processed.py | 10 +- solidago/src/solidago/state/models/scaled.py | 6 +- .../tests/load_save/test_tiny_tournesol.py | 4 +- .../tests/save_tiny_tournesol/comparisons.csv | 4538 ++++++++--------- .../tests/save_tiny_tournesol/entities.csv | 920 ++-- 26 files changed, 3152 insertions(+), 3231 deletions(-) delete mode 100644 solidago/src/solidago/pipeline/post_process/no_post_process.py diff --git a/solidago/src/solidago/pipeline/__init__.py b/solidago/src/solidago/pipeline/__init__.py index 322c2a26d2..78e1422c8c 100644 --- a/solidago/src/solidago/pipeline/__init__.py +++ b/solidago/src/solidago/pipeline/__init__.py @@ -1,9 +1,9 @@ from .trust_propagation import * -# from .preference_learning import * +from .preference_learning import * from .voting_rights import * # from .scaling import * -# from .aggregation import * -# from .post_process import * +from .aggregation import * +from .post_process import * from .base import * from .sequential import * diff --git a/solidago/src/solidago/pipeline/aggregation/__init__.py b/solidago/src/solidago/pipeline/aggregation/__init__.py index 69622dca41..18df0e3812 100644 --- a/solidago/src/solidago/pipeline/aggregation/__init__.py +++ b/solidago/src/solidago/pipeline/aggregation/__init__.py @@ -7,5 +7,5 @@ from .base import Aggregation from .average import Average from .entitywise_qr_quantile import EntitywiseQrQuantile -from .standardized_qr_quantile import StandardizedQrQuantile -from .standardized_qr_median import StandardizedQrMedian +# from .standardized_qr_quantile import StandardizedQrQuantile +# from .standardized_qr_median import StandardizedQrMedian diff --git a/solidago/src/solidago/pipeline/aggregation/average.py b/solidago/src/solidago/pipeline/aggregation/average.py index cf4b67ded4..a7c5b598b0 100644 --- a/solidago/src/solidago/pipeline/aggregation/average.py +++ b/solidago/src/solidago/pipeline/aggregation/average.py @@ -7,57 +7,47 @@ class Average(Aggregation): - def __call__( - self, + def main(self, + entities: Entities, voting_rights: VotingRights, - user_models: dict[int, ScoringModel], - users: pd.DataFrame, - entities: pd.DataFrame - ) -> tuple[dict[int, ScoringModel], ScoringModel]: - """ Returns scaled user models - - Parameters - ---------- - voting_rights: VotingRights - voting_rights[user, entity]: float - user_models: dict[int, ScoringModel] - user_models[user] is user's scoring model - users: DataFrame with columns - * user_id (int, index) - * trust_score (float) - entities: DataFrame with columns - * entity_id (int, ind) - - Returns - ------- - updated_user_models[user]: ScoringModel - Returns a scaled user model - global_model: ScoringModel - Returns a global scoring model - """ + user_models: UserModels, + ) -> ScoringModel: + """ Returns weighted average of user's scores """ global_model = DirectScoringModel() + voting_rights = voting_rights.reorder_keys(["username", "entity_name", "criterion"]) - for entity in entities.index: + for entity in entities: - total_voting_rights, total_scores = 0, 0 - total_lefts, total_rights = 0, 0 + total_voting_rights, total_scores = dict(), dict() + total_lefts, total_rights = dict(), dict() - for user in user_models: - output = user_models[user](entity, entities.loc[entity]) - if output is None: - continue - total_voting_rights += voting_rights[user, entity] - total_scores = voting_rights[user, entity] * output[0] - total_lefts = voting_rights[user, entity] * output[1] - total_rights = voting_rights[user, entity] * output[2] + for user, model in user_models: + multiscore = model(entity) + + for criterion, score in multiscore: - if total_voting_rights == 0: - continue + if score.isnan(): + continue - score = total_scores / total_voting_rights - left = total_lefts / total_voting_rights - right = total_rights / total_voting_rights - global_model[entity] = score, left, right + for d in (total_voting_rights, total_scores, total_lefts, total_rights): + if criterion not in d: + d[criterion] = 0 - return user_models, global_model + total_voting_rights[criterion] += voting_rights[user, entity, criterion] + total_scores[criterion] = voting_rights[user, entity, criterion] * output[0] + total_lefts[criterion] = voting_rights[user, entity, criterion] * output[1] + total_rights[criterion] = voting_rights[user, entity, criterion] * output[2] + + for criterion in total_voting_rights: + + if total_voting_rights[criterion] == 0: + continue + + global_model[entity, criterion] = ( + total_scores[criterion] / total_voting_rights[criterion], + total_lefts[criterion] / total_voting_rights[criterion], + total_rights[criterion] / total_voting_rights[criterion], + ) + + return global_model diff --git a/solidago/src/solidago/pipeline/aggregation/entitywise_qr_quantile.py b/solidago/src/solidago/pipeline/aggregation/entitywise_qr_quantile.py index e0e8b2b09a..ec3e9b2900 100644 --- a/solidago/src/solidago/pipeline/aggregation/entitywise_qr_quantile.py +++ b/solidago/src/solidago/pipeline/aggregation/entitywise_qr_quantile.py @@ -3,10 +3,8 @@ from .base import Aggregation -from solidago.voting_rights import VotingRights -from solidago.scoring_model import ScoringModel, DirectScoringModel - -from solidago.primitives import qr_quantile, qr_uncertainty +from solidago.state import * +from solidago.primitives.lipschitz import qr_quantile, qr_uncertainty class EntitywiseQrQuantile(Aggregation): @@ -25,90 +23,69 @@ def __init__(self, quantile=0.2, lipschitz=0.1, error=1e-5): self.lipschitz = lipschitz self.error = error - def __call__( - self, + def main(self, + entities: Entities, voting_rights: VotingRights, - user_models: dict[int, ScoringModel], - users: pd.DataFrame, - entities: pd.DataFrame - ) -> tuple[dict[int, ScoringModel], ScoringModel]: - """ Returns scaled user models - - Parameters - ---------- - voting_rights: VotingRights - voting_rights[user, entity]: float - user_models: dict[int, ScoringModel] - user_models[user] is user's scoring model - users: DataFrame with columns - * user_id (int, index) - * trust_score (float) - entities: DataFrame with columns - * entity_id (int, ind) - - Returns - ------- - updated_user_models[user]: ScoringModel - Returns a scaled user model - global_model: ScoringModel - Returns a global scoring model - """ - df = _get_user_scores(voting_rights, user_models, entities) + user_models: UserModels, + ) -> ScoringModel: + """ Returns scaled user models """ global_scores = DirectScoringModel() - for entity_id, dfe in df.groupby("entity_id"): - score = qr_quantile( - self.lipschitz, - self.quantile, - np.array(dfe["scores"]), - np.array(dfe["voting_rights"]), - np.array(dfe["left_uncertainties"]), - np.array(dfe["right_uncertainties"]), - self.error - ) - uncertainty = qr_uncertainty( - self.lipschitz, - np.array(dfe["scores"]), - np.array(dfe["voting_rights"]), - np.array(dfe["left_uncertainties"]), - np.array(dfe["right_uncertainties"]), - default_dev = 1.0, - error = self.error, - median = score if self.quantile == 0.5 else None, - ) - global_scores[entity_id] = score, uncertainty + voting_rights = voting_rights.reorder_keys(["entity_name", "username", "criterion"]) + for entity in entities: + all_scores = self.get_scores(entity, user_models) + rights = self.get_voting_rights(entity, voting_rights, user_models) + for criterion, scores_list in all_scores.items(): + if criterion not in rights: + continue + scores, left_uncs, right_uncs = [ np.array(l) for l in zip(*scores_list)) ] + score = qr_quantile( + lipschitz=self.lipschitz, + quantile=self.quantile, + values=scores, + voting_rights=np.array(rights[criterion]), + left_uncertainties=left_uncs, + right_uncertainties=right_uncs, + error=self.error + ) + uncertainty = qr_uncertainty( + lipschitz=self.lipschitz, + values=np.array(dfe["scores"]), + voting_rights=np.array(dfe["voting_rights"]), + left_uncertainties=np.array(dfe["left_uncertainties"]), + right_uncertainties=np.array(dfe["right_uncertainties"]), + default_dev=1.0, + error=self.error, + median = score if self.quantile == 0.5 else None, + ) + global_scores[entity, criterion] = score, uncertainty, uncertainty - return user_models, global_scores - - def to_json(self): - return type(self).__name__, dict(quantile=self.quantile, - lipschitz=self.lipschitz, error=self.error) - - def __str__(self): - prop_names = ["quantile", "lipschitz", "error"] - prop = ", ".join([f"{p}={getattr(self, p)}" for p in prop_names]) - return f"{type(self).__name__}({prop})" - - -def _get_user_scores( - voting_rights: VotingRights, - user_models: dict[int, ScoringModel], - entities: pd.DataFrame -): - user_list, entity_list, voting_right_list = list(), list(), list() - scores, lefts, rights = list(), list(), list() - for user in user_models: - for entity in user_models[user].scored_entities(entities): - user_list.append(user) - entity_list.append(entity) - voting_right_list.append(voting_rights[user, entity]) - output = user_models[user](entity, entities.loc[entity]) - scores.append(output[0]) - lefts.append(output[1]) - rights.append(output[2]) - - return pd.DataFrame(dict( - user_id=user_list, entity_id=entity_list, voting_rights=voting_right_list, - scores=scores, left_uncertainties=lefts, right_uncertainties=rights - )) + return global_scores + def get_scores(self, + entity: Entity, + user_models: UserModels, + ) -> dict[str, list[MultiScore]]: + """ Collect all user's multiscores of entity """ + scores = dict() + for _, model in user_models: + multiscore = model(entity) + for criterion, score in multiscore: + if criterion not in scores: + scores[criterion] = list() + scores[criterion].append(score.to_triplet()) + return scores + + def get_voting_rights(self, + entity: Entity, + voting_rights: VotingRights, + user_models: UserModels + ) -> dict[str, list[float]]: + result = dict() + voting_rights = voting_rights.reorder_keys(["entity_name", "username", "criterion"]) + for username, _ in user_models: + for criterion, value in voting_rights[entity, username]: + if criterion not in result: + result[criterion] = list() + result[criterion].append(value) + return result diff --git a/solidago/src/solidago/pipeline/pipeline.py b/solidago/src/solidago/pipeline/pipeline.py index 6d6e7ee39b..fa9f7a055b 100644 --- a/solidago/src/solidago/pipeline/pipeline.py +++ b/solidago/src/solidago/pipeline/pipeline.py @@ -9,24 +9,19 @@ logger = logging.getLogger(__name__) from solidago.state import State +from .base import StateFunction from .sequential import Sequential from .identity import Identity -from .trust_propagation import TrustPropagation -from .voting_right import VotingRights -from .preference_learning import PreferenceLearning -from .scaling import Scaling -from .aggregation import Aggregation -from .post_process import PostProcess class Pipeline(Sequential): def __init__(self, - trust_propagation: TrustPropagation=TrustPropagation(), - voting_rights_assignment: VotingRightsAssignment=VotingRightsAssignment(), - preference_learning: PreferenceLearning=PreferenceLearning(), - scaling: Scaling=Scaling(), - aggregation: Aggregation=Aggregation(), - post_process: PostProcess=PostProcess(), + trust_propagation: StateFunction=Identity(), + voting_rights_assignment: StateFunction=Identity(), + preference_learning: StateFunction=Identity(), + scaling: StateFunction=Identity(), + aggregation: StateFunction=Identity(), + post_process: StateFunction=Identity(), ): """Instantiates the pipeline components. diff --git a/solidago/src/solidago/pipeline/post_process/base.py b/solidago/src/solidago/pipeline/post_process/base.py index 3072b8f912..92f786cc53 100644 --- a/solidago/src/solidago/pipeline/post_process/base.py +++ b/solidago/src/solidago/pipeline/post_process/base.py @@ -3,33 +3,14 @@ import pandas as pd -from solidago.scoring_model import ScoringModel +from solidago.state import * -class PostProcess(ABC): - @abstractmethod - def __call__( - self, - user_models: Mapping[int, ScoringModel], +class PostProcess(StateFunction): + def main(self, + user_models: UserModels, global_model: ScoringModel, - entities: pd.DataFrame - ) -> tuple[Mapping[int, ScoringModel], ScoringModel]: + ) -> tuple[UserModels, ScoringModel]: """ Post-processes user models and global models, - typically to yield human-readible scores - - Parameters - ---------- - user_models: user_model[user] should be a ScoringModel to post-process - global_model: ScoringModel to post-process - entities: DataFrame with columns - * entity_id (int, index) - - Returns - ------- - user_models: post-processed user models - global_model: post-processed global model - """ - raise NotImplementedError - - def to_json(self) -> tuple: - return (type(self).__name__, ) + typically to yield human-readible scores """ + return user_models, global_model diff --git a/solidago/src/solidago/pipeline/post_process/no_post_process.py b/solidago/src/solidago/pipeline/post_process/no_post_process.py deleted file mode 100644 index 0f6ea50dba..0000000000 --- a/solidago/src/solidago/pipeline/post_process/no_post_process.py +++ /dev/null @@ -1,29 +0,0 @@ -import pandas as pd - -from solidago.scoring_model import ScoringModel -from .base import PostProcess - - -class NoPostProcess(PostProcess): - def __call__( - self, - user_models: dict[int, ScoringModel], - global_model: ScoringModel, - entities: pd.DataFrame - ) -> tuple[dict[int, ScoringModel], ScoringModel]: - """ Post-processes user models and global models, - typically to yield human-readible scores - - Parameters - ---------- - user_models: user_model[user] should be a ScoringModel to post-process - global_model: ScoringModel to post-process - entities: DataFrame with columns - * entity_id (int, index) - - Returns - ------- - user_models: post-processed user models - global_model: post-processed global model - """ - return user_models, global_model diff --git a/solidago/src/solidago/pipeline/post_process/squash.py b/solidago/src/solidago/pipeline/post_process/squash.py index 66c97fc56a..e70b7d6957 100644 --- a/solidago/src/solidago/pipeline/post_process/squash.py +++ b/solidago/src/solidago/pipeline/post_process/squash.py @@ -3,43 +3,25 @@ import numpy as np import pandas as pd +from solidago.state import * from .base import PostProcess -from solidago.scoring_model import ScoringModel, PostProcessedScoringModel class Squash(PostProcess): def __init__(self, score_max: float = 100.0): + assert score_max > 0 self.score_max = score_max - def __call__( - self, - user_models: Mapping[int, ScoringModel], + def main(self, + user_models: UserModels, global_model: ScoringModel, - entities: Optional[pd.DataFrame] = None - ) -> tuple[Mapping[int, ScoringModel], ScoringModel]: + ) -> tuple[UserModels, ScoringModel]: """ Post-processes user models and global models, - typically to yield human-readible scores - - Parameters - ---------- - user_models: user_model[user] should be a ScoringModel to post-process - global_model: ScoringModel to post-process - entities: DataFrame with columns - * entity_id (int, index) - - Returns - ------- - user_models: post-processed user models - global_model: post-processed global model - """ - squash = lambda x: self.score_max * x / np.sqrt( 1 + x**2 ) - - squashed_user_models = { - u: PostProcessedScoringModel(user_models[u], squash) - for u in user_models - } - squashed_global_model = PostProcessedScoringModel(global_model, squash) + typically to yield human-readible scores, + by squashing scores into [-self.score_max, self.score_max] """ + squashed_user_models = UserModels({ + username: SquashedModel(model, self.score_max) + for username, model in user_models + }) + squashed_global_model = SquashedModel(global_model, squash) return squashed_user_models, squashed_global_model - - def to_json(self): - return (type(self).__name__, dict(score_max=self.score_max)) diff --git a/solidago/src/solidago/pipeline/preference_learning/base.py b/solidago/src/solidago/pipeline/preference_learning/base.py index 2a65d9ad24..32fd74e510 100644 --- a/solidago/src/solidago/pipeline/preference_learning/base.py +++ b/solidago/src/solidago/pipeline/preference_learning/base.py @@ -20,13 +20,15 @@ def main(self, ) -> UserModels: """ Learns a scoring model, given user judgments of entities """ learned_models = UserModels() + comparison_key_names = ["user", "criterion", "left_name", "right_name"] + reordered_comparisons = comparisons.reorder_keys(comparison_key_names) for user in users: learned_models[user] = self.user_learn( user, entities, assessments[user], comparisons[user], - user_models[user].base_model() if user in user_models else None + user_models[user].base_model() if user in user_models else DirectScoring() ) return learned_models diff --git a/solidago/src/solidago/pipeline/preference_learning/generalized_bradley_terry.py b/solidago/src/solidago/pipeline/preference_learning/generalized_bradley_terry.py index 23364682a0..b8004c7066 100644 --- a/solidago/src/solidago/pipeline/preference_learning/generalized_bradley_terry.py +++ b/solidago/src/solidago/pipeline/preference_learning/generalized_bradley_terry.py @@ -8,7 +8,7 @@ from numba import njit from solidago.state import * -from solidago.solvers.optimize import coordinate_descent, njit_brentq +from solidago.primitives.optimize import coordinate_descent, njit_brentq from .base import PreferenceLearning @@ -20,14 +20,27 @@ def __init__( high_likelihood_range_threshold: float=1.0, max_uncertainty: float=1e3 ): - """ + """ Generalized Bradley Terry is a class of porbability models of comparisons, + introduced in the paper "Generalized Bradley-Terry Models for Score Estimation + from Paired Comparisons" by Julien Fageot, Sadegh Farhadkhani, Lê-Nguyên Hoang + and Oscar Villemaud, and published at AAAI'24. + + This implementation leverages coordinate descent, and makes heavy use of numba + to accelerate the computations. Parameters ---------- - initialization: dict[int, float] - previously computed entity scores - error: float - tolerated error + prior_std_dev: float=7.0 + Typical scale of scores. + Technical, it should be the standard deviation of the gaussian prior. + convergence_error: float=1e-5 + Admissible error in score computations (obtained through optimization). + high_likelihood_range_threshold: float=1.0 + To determine the uncertainty, we compute left_unc (respectively, right_unc) + such that score - left_unc (respectively, + right_unc) has a likelihood + which is exp(high_likelihood_range_threshold) times lower than score. + max_uncertainty: float=1e3 + Replaces infinite uncertainties with max_uncertainty """ self.prior_std_dev = prior_std_dev self.convergence_error = convergence_error @@ -94,37 +107,71 @@ def f(derivative_args, old_coordinate_value): ) return f - def initialize_entity_scores(self, base_model, entities, entity_names) -> np.ndarray: - scores = np.zeros(len(entities)) - if initialization is not None: - for index, entity_name in enumerate(entity_names): - score = initialization(entities.get(entity_name)) - if not score.isnan(): - scores[index] = score.value - return scores - def user_learn(self, user: User, entities: Entities, assessments: Assessments, comparisons: Comparisons, - base_model: Optional[BaseModel]=None, + base_model: BaseModel, ) -> BaseModel: """ Learns only based on comparisons """ model = DirectScoring() + reordered_direct_scoring = base_model.to_direct().reorder_keys(["criterion", "entity_name"]) for criterion in comparisons.get_set("criterion", "default"): - entity_scores = self.user_learn_criterion(user, entities, comparisons, base_model, criterion) + entity_scores = self.user_learn_criterion( + user, + reordered_comparisons[{"criterion": criterion }], + reordered_direct_scoring[criterion] + ) for index, (entity_name, score) in enumerate(entity_scores.items()): model[entity_name].add_row(dict(criterion=criterion) | score.to_dict()) return model + + def init_solution(self, + init_model: DirectScoring, + entity_names: list[str], + entity_name2index: dict[str, int] + ) -> np.ndarray: + scores = np.zeros(len(entity_names)) + if initialization is not None: + for index, entity_name in enumerate(entity_names): + score = init_model(entity_name) + if not score.isnan(): + scores[index] = score.value + return scores + + def compute_scores_without_uncertainties(self, + comparisons: Comparisons, + direct_scoring: DirectScoring, + entity_names: list[str], + entity_name2index: dict[str, int], + ) -> npt.NDArray: + """ Computes the scores given comparisons """ + entity_ordered_comparisons = comparisons.order_by_entities() + def get_derivative_args(entity_index: int, solution: np.ndarray): + entity_name = entity_names[entity_index] + df = entity_ordered_comparisons[entity_name].to_df() + values = dict() + for _, row in df.iterrows(): + values[ entity_name2index[row["with"]] ] = row["comparison"] / row["comparison_max"] + values = list(zip(*values.values())) + indices = np.array(list(values.keys())) + comparison_values = np.array(list(values.values())) + return solution[indices], comparison_values + + init_solution = self.init_solution(direct_scoring, entity_names, entity_name2index) + return coordinate_descent( + self.update_coordinate_function, + get_args=get_derivative_args, + initialization=init_solution, + updated_coordinates=list(), + error=self.convergence_error, + ) def user_learn_criterion(self, user: User, - entities: Entities, - assessments: Assessments, comparisons: Comparisons, - base_model: Optional[BaseModel]=None, - criterion: str + direct_scoring: DirectScoring ) -> dict[str, Score]: """ Returns @@ -133,41 +180,30 @@ def user_learn_criterion(self, out[entity_name] must be of type Score (i.e. with a value and left/right uncertainties """ entity_names = list(comparisons.get_set("left_name") | comparisons.get_set("right_name")) - entity_name2index = { entity: c for c, entity in enumerate(entities) } - entity_ordered_comparisons = comparisons.order_by_entities() + entity_name2index = { entity_name: c for c, entity_name in enumerate(entity_names) } - comparisons_dict = self.comparisons_dict(comparisons, entity_coordinates) - - - updated_coordinates = list() - - def get_derivative_args(entity_index: int, solution: np.ndarray): - indices, comparisons_bis = comparisons_dict[entity_index] - return solution[indices],comparisons_bis - - solution = coordinate_descent( - self.update_coordinate_function, - get_args=get_derivative_args, - initialization=init_solution, - updated_coordinates=updated_coordinates, - error=self.convergence_error, + solution = self.compute_scores_without_uncertainties( + comparisons, + direct_scoring, + entity_names, + entity_name2index ) - - comparisons = comparisons.assign( - entity_a_coord=comparisons["entity_a"].map(entity_coordinates), - entity_b_coord=comparisons['entity_b'].map(entity_coordinates), + + comparisons_df = comparisons.to_df().assign( + left_index=comparisons["left_name"].map(entity_name2index), + right_index=comparisons['right_name'].map(entity_name2index), ) - score_diff = solution[comparisons["entity_a_coord"]] - solution[comparisons["entity_b_coord"]] - r_actual = (comparisons["comparison"] / comparisons["comparison_max"]).to_numpy() + score_diff = solution[comparisons_df["left_index"]] - solution[comparisons_df["right_index"]] + comparisons_np = (comparisons_df["comparison"] / comparisons_df["comparison_max"]).to_numpy() uncertainties_left = np.empty_like(solution) uncertainties_right = np.empty_like(solution) - ll_actual = self.log_likelihood_function(score_diff, r_actual) + ll_actual = self.log_likelihood_function(score_diff, comparisons_np) for coordinate in range(len(solution)): comparison_indicator = ( - (comparisons["entity_a_coord"] == coordinate).astype(int) - - (comparisons["entity_b_coord"] == coordinate).astype(int) + (comparisons["left_index"] == coordinate).astype(int) + - (comparisons["right_index"] == coordinate).astype(int) ).to_numpy() try: uncertainties_left[coordinate] = -1 * njit_brentq( @@ -194,37 +230,10 @@ def get_derivative_args(entity_index: int, solution: np.ndarray): uncertainties_right[coordinate] = self.max_uncertainty model = DirectScoringModel() - for coord in range(len(solution)): - model[entities[coord]] = solution[coord], uncertainties_left[coord], uncertainties_right[coord] + for i in range(len(solution)): + model[entity_names[i]] = solution[i], uncertainties_left[i], uncertainties_right[i] return model - def comparisons_dict(self, comparisons, entity_coordinates) -> dict[int, tuple[npt.NDArray, npt.NDArray]]: - comparisons = comparisons[["entity_a","entity_b","comparison", "comparison_max"]] - comparisons_sym = pd.concat( - [ - comparisons, - pd.DataFrame( - { - "entity_a": comparisons.entity_b, - "entity_b": comparisons.entity_a, - "comparison": -1 * comparisons.comparison, - "comparison_max": comparisons.comparison_max, - } - ), - ] - ) - comparisons_sym.entity_a = comparisons_sym.entity_a.map(entity_coordinates) - comparisons_sym.entity_b = comparisons_sym.entity_b.map(entity_coordinates) - comparisons_sym.comparison = -1 * np.where( - np.isfinite(comparisons_sym.comparison_max), - comparisons_sym.comparison / comparisons_sym.comparison_max, - comparisons_sym.comparison - ) - return { - coord: (group["entity_b"].to_numpy(), group["comparison"].to_numpy()) - for (coord, group) in comparisons_sym.groupby("entity_a") - } # type: ignore - @cached_property def partial_derivative(self): """ Computes the partial derivative along a coordinate, @@ -306,16 +315,3 @@ def f(score_diff: npt.NDArray): ) return f - - def to_json(self): - return type(self).__name__, dict( - prior_std_dev=self.prior_std_dev, - convergence_error=self.convergence_error, - cumulant_generating_function_error=self.cumulant_generating_function_error, - high_likelihood_range_threshold=self.high_likelihood_range_threshold, - ) - - def __str__(self): - prop_names = ["prior_std_dev", "convergence_error", "cumulant_generating_function_error"] - prop = ", ".join([f"{p}={getattr(self, p)}" for p in prop_names]) - return f"{type(self).__name__}({prop})" diff --git a/solidago/src/solidago/pipeline/preference_learning/lbfgs_generalized_bradley_terry.py b/solidago/src/solidago/pipeline/preference_learning/lbfgs_generalized_bradley_terry.py index 8fcbeab81c..996a897ea3 100644 --- a/solidago/src/solidago/pipeline/preference_learning/lbfgs_generalized_bradley_terry.py +++ b/solidago/src/solidago/pipeline/preference_learning/lbfgs_generalized_bradley_terry.py @@ -12,31 +12,49 @@ "Install 'solidago[torch]' to get the optional dependencies." ) from exc -from solidago.scoring_model import ScoringModel, DirectScoringModel -from solidago.solvers import dichotomy -from .comparison_learning import ComparisonBasedPreferenceLearning +from solidago.state import * +from solidago.primitives import dichotomy +from .base import PreferenceLearning -class LBFGSGeneralizedBradleyTerry(ComparisonBasedPreferenceLearning): - def __init__( - self, - prior_std_dev: float = 7, - convergence_error: float = 1e-5, - max_iter: int = 100, - high_likelihood_range_threshold = 1.0, + +class LBFGSGeneralizedBradleyTerry(PreferenceLearning): + def __init__(self, + prior_std_dev: float=7, + convergence_error: float=1e-5, + high_likelihood_range_threshold: float=1.0, + max_uncertainty: float=1e3, + max_iter: int=100, ): - """ + """ Generalized Bradley Terry is a class of porbability models of comparisons, + introduced in the paper "Generalized Bradley-Terry Models for Score Estimation + from Paired Comparisons" by Julien Fageot, Sadegh Farhadkhani, Lê-Nguyên Hoang + and Oscar Villemaud, and published at AAAI'24. + + This implementation leverages the pytorch implementation of the Limited-memory + Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm, a second-order quasi-Newton + method with limited demands of computer memory. Parameters ---------- - initialization: dict[int, float] - previously computed entity scores - error: float - tolerated error + prior_std_dev: float=7.0 + Typical scale of scores. + Technical, it should be the standard deviation of the gaussian prior. + convergence_error: float=1e-5 + Admissible error in score computations (obtained through optimization). + high_likelihood_range_threshold: float=1.0 + To determine the uncertainty, we compute left_unc (respectively, right_unc) + such that score - left_unc (respectively, + right_unc) has a likelihood + which is exp(high_likelihood_range_threshold) times lower than score. + max_uncertainty: float=1e3 + Replaces infinite uncertainties with max_uncertainty + max_iter: int=100 + Maximal number of iterations used """ self.prior_std_dev = prior_std_dev self.convergence_error = convergence_error - self.max_iter = max_iter self.high_likelihood_range_threshold = high_likelihood_range_threshold + self.max_uncertainty = max_uncertainty + self.max_iter = max_iter self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") @abstractmethod @@ -47,61 +65,72 @@ def cumulant_generating_function(self, score_diff: torch.Tensor) -> torch.Tensor Parameters ---------- - score_diff: float - Score difference + score_diff: torch.Tensor + Score differences Returns ------- - out: float + out: torch.Tensor + values of the cumulant generating function on the score differences """ pass - def comparison_learning( - self, - comparisons: pd.DataFrame, - entities=None, - initialization: Optional[ScoringModel] = None, - updated_entities: Optional[set[int]] = None, - ) -> ScoringModel: - """Learns only based on comparisons + def user_learn(self, + user: User, + entities: Entities, + assessments: Assessments, + comparisons: Comparisons, + base_model: BaseModel, + ) -> BaseModel: + """ Learns only based on comparisons """ + model = DirectScoring() + reordered_direct_scoring = base_model.to_direct().reorder_keys(["criterion", "entity_name"]) + for criterion in comparisons.get_set("criterion", "default"): + entity_scores = self.user_learn_criterion( + user, + reordered_comparisons[{"criterion": criterion }], + reordered_direct_scoring[criterion] + ) + for index, (entity_name, score) in enumerate(entity_scores.items()): + model[entity_name].add_row(dict(criterion=criterion) | score.to_dict()) + return model - Parameters - ---------- - comparisons: DataFrame with columns - * entity_a: int - * entity_b: int - * comparison: float - * comparison_max: float - entities: DataFrame - This parameter is not used - """ - if len(comparisons) == 0: - return DirectScoringModel() + def init_solution(self, + init_model: DirectScoring, + entity_names: list[str], + entity_name2index: dict[str, int] + ) -> torch.Tensor: + scores = torch.zeros(len(entity_names)) + if initialization is not None: + for index, entity_name in enumerate(entity_names): + score = init_model(entity_name) + if not score.isnan(): + scores[index] = score.value + return scores - entities = list(set(comparisons["entity_a"]) | set(comparisons["entity_b"])) - entity_coordinates = {entity: c for c, entity in enumerate(entities)} - comparisons_np = ( - comparisons["entity_a"].map(entity_coordinates).to_numpy(), - comparisons["entity_b"].map(entity_coordinates).to_numpy(), - (comparisons["comparison"] / comparisons["comparison_max"]).to_numpy() + def compute_scores_without_uncertainties(self, + comparisons: Comparisons, + direct_scoring: DirectScoring, + entity_names: list[str], + entity_name2index: dict[str, int], + ) -> torch.Tensor: + """ Computes the scores given comparisons """ + comparisons_df = comparisons.to_df().assign( + left_index=comparisons["left_name"].map(entity_name2index), + right_index=comparisons['right_name'].map(entity_name2index), + normalized_comparisons=(comparisons['comparison'] / comparisons['comparison_max']) ) + solution = self.init_solution(direct_scoring, entity_names, entity_name2index) + solution.requires_grad = True + solution = solution.to(self.device) - solution = np.random.normal(0.0, 1.0, size=len(entities)) - if initialization is not None: - for (entity_id, values) in initialization.iter_entities(): - entity_coord = entity_coordinates.get(entity_id) - if entity_coord is not None: - score, _left, _right = values - solution[entity_coord] = score - - solution = torch.tensor(solution, requires_grad=True, device=self.device) lbfgs = torch.optim.LBFGS( (solution,), max_iter=self.max_iter, tolerance_change=self.convergence_error, line_search_fn="strong_wolfe", ) - + def closure(): lbfgs.zero_grad() loss = self.loss(solution, comparisons_np) @@ -117,6 +146,32 @@ def closure(): solution = solution.detach() if solution.isnan().any(): raise RuntimeError(f"Nan in solution, state: {lbfgs.state_dict()}") + return solution + + def user_learn_criterion(self, + user: User, + comparisons: Comparisons, + direct_scoring: DirectScoring + ) -> dict[str, Score]: + if len(comparisons) == 0: + return DirectScoringModel() + + entity_names = list(comparisons.get_set("left_name") | comparisons.get_set("right_name")) + entity_name2index = { entity_name: c for c, entity_name in enumerate(entity_names) } + + solution = self.compute_scores_without_uncertainties( + comparisons, + direct_scoring, + entity_names, + entity_name2index + ) + + comparisons_df = comparisons.to_df().assign( + left_index=comparisons["left_name"].map(entity_name2index), + right_index=comparisons['right_name'].map(entity_name2index), + ) + score_diff = solution[comparisons_df["left_index"]] - solution[comparisons_df["right_index"]] + comparisons_np = (comparisons_df["comparison"] / comparisons_df["comparison_max"]).to_numpy() def loss_with_delta(delta, comparisons, coord): solution_with_delta = solution.clone() @@ -153,7 +208,7 @@ def loss_with_delta(delta, comparisons, coord): except ValueError: uncertainty_right = self.MAX_UNCERTAINTY - model[entities[coordinate]] = ( + model[entity_names[coordinate]] = ( solution[coordinate].item(), uncertainty_left, uncertainty_right, diff --git a/solidago/src/solidago/pipeline/scaling/quantile_zero_shift.py b/solidago/src/solidago/pipeline/scaling/quantile_zero_shift.py index c8193f1678..5c9df48c22 100644 --- a/solidago/src/solidago/pipeline/scaling/quantile_zero_shift.py +++ b/solidago/src/solidago/pipeline/scaling/quantile_zero_shift.py @@ -12,15 +12,13 @@ class QuantileShift(Scaling): - def __init__( - self, + def __init__(self, quantile: float = 0.15, - *, target_score: float = 0.0, lipschitz: float = 0.1, error: float = 1e-5, ): - """The scores are shifted so that their quantile zero_quantile equals zero + """ The scores are shifted so that their quantile zero_quantile equals zero Parameters ---------- @@ -31,81 +29,46 @@ def __init__( self.lipschitz = lipschitz self.error = error - def __call__( - self, - user_models: Mapping[int, ScoringModel], - users: pd.DataFrame, - entities: pd.DataFrame, - voting_rights: VotingRights, - privacy: PrivacySettings, - ) -> dict[int, ScaledScoringModel]: - """Returns scaled user models - - Parameters - ---------- - user_models: dict[int, ScoringModel] - user_models[user] is user's scoring model - users: DataFrame with columns - * user_id (int, index) - * trust_score (float) - entities: DataFrame with columns - * entity_id (int, ind) - voting_rights: VotingRights - voting_rights[user, entity]: float - privacy: PrivacySettings - privacy[user, entity] in { True, False, None } - + def main(self, entities: Entities, user_models: UserModels) -> UserModels: + """ Returns scaled user models + Returns ------- out[user]: ScoringModel Will be scaled by the Scaling method """ - weights = [] - scores, lefts, rights = [], [], [] - for user_id, user_model in user_models.items(): - n_entities = 0 - for entity_id, output in user_model.iter_entities(entities): - n_entities += 1 - scores.append(output[0]) - lefts.append(output[1]) - rights.append(output[2]) - if n_entities > 0: - weights.extend([1 / n_entities] * n_entities) - - shift = -qr_quantile( - lipschitz=self.lipschitz, - quantile=self.quantile, - values=np.array(scores), - voting_rights=np.array(weights), - left_uncertainties=np.array(lefts), - right_uncertainties=np.array(rights), - error=self.error, - ) + self.target_score - - return { + values, criteria = dict(), set() + for username, model in user_models: + for entity in entities: + multiscore = model(entity) + for criterion, score in multiscore: + if criterion not in values: + values[criterion] = list() + criteria.add(criterion) + values[criterion].append(score.to_triplet()) + + for criterion in criteria: + scores, lefts, rights = zip(*values[criterion]) + shift = - qr_quantile( + lipschitz=self.lipschitz, + quantile=self.quantile, + values=np.array(scores), + voting_rights=np.array([1/len(entities)] * len(entities)), + left_uncertainties=np.array(lefts), + right_uncertainties=np.array(rights), + error=self.error, + ) + self.target_score + + return UserModels({ user: ScaledScoringModel(user_model, translation=shift) for (user, user_model) in user_models.items() - } - - def to_json(self): - return type(self).__name__, dict( - quantile=self.quantile, - target_score=self.target_score, - lipschitz=self.lipschitz, - error=self.error - ) - - def __str__(self): - prop_names = ["quantile", "lipschitz", "error", "target_score"] - prop = ", ".join([f"{p}={getattr(self, p)}" for p in prop_names]) - return f"{type(self).__name__}({prop})" + }) class QuantileZeroShift(QuantileShift): def __init__( self, zero_quantile: float = 0.15, - *, lipschitz: float = 0.1, error: float = 0.00001 ): diff --git a/solidago/src/solidago/pipeline/scaling/standardize.py b/solidago/src/solidago/pipeline/scaling/standardize.py index bff2534430..2f00f558c5 100644 --- a/solidago/src/solidago/pipeline/scaling/standardize.py +++ b/solidago/src/solidago/pipeline/scaling/standardize.py @@ -14,20 +14,19 @@ def __init__(self, dev_quantile: float=0.9, lipschitz: float=0.1, error: float=1 Parameters ---------- - zero_quantile: float + dev_quantile: float """ self.dev_quantile = dev_quantile self.lipschitz = lipschitz self.error = error - def __call__( - self, - user_models: dict[int, ScoringModel], - users: pd.DataFrame, - entities: pd.DataFrame, + def main(self, + users: Users, + entities: Entities, + made_public: MadePublic, voting_rights: VotingRights, - privacy: PrivacySettings - ): + user_models: UserModels, + ) -> UserModels: df = _get_user_scores(user_models, entities) std_dev = self._compute_std_dev(df) return { @@ -48,15 +47,6 @@ def _compute_std_dev(self, df): error=self.error, ) - def to_json(self): - return type(self).__name__, dict(dev_quantile=self.dev_quantile, - lipschitz=self.lipschitz, error=self.error) - - def __str__(self): - prop_names = ["dev_quantile", "lipschitz", "error"] - prop = ", ".join([f"{p}={getattr(self, p)}" for p in prop_names]) - return f"{type(self).__name__}({prop})" - def _get_user_scores(user_models: dict[int, ScoringModel], entities: pd.DataFrame): user_list, entity_list = list(), list() diff --git a/solidago/src/solidago/pipeline/trust_propagation/base.py b/solidago/src/solidago/pipeline/trust_propagation/base.py index a480d8a7ab..5b0e8a99df 100644 --- a/solidago/src/solidago/pipeline/trust_propagation/base.py +++ b/solidago/src/solidago/pipeline/trust_propagation/base.py @@ -7,6 +7,6 @@ class TrustPropagation(StateFunction): @abstractmethod def main(self, users: Users, vouches: Vouches) -> Users: - """ Propagates user trust through vouches, and stores result in state.users """ + """ Propagates user trust through vouches """ return self.propagate(state.users, state.vouches) diff --git a/solidago/src/solidago/pipeline/voting_rights/base.py b/solidago/src/solidago/pipeline/voting_rights/base.py index 44479f8977..ca622e2585 100644 --- a/solidago/src/solidago/pipeline/voting_rights/base.py +++ b/solidago/src/solidago/pipeline/voting_rights/base.py @@ -4,4 +4,4 @@ class VotingRightsAssignment(StateFunction): def main(self, voting_rights: VotingRights) -> VotingRights: - return state.voting_rights + return voting_rights diff --git a/solidago/src/solidago/primitives/datastructure/nested_dict.py b/solidago/src/solidago/primitives/datastructure/nested_dict.py index 4e4bfe47b5..c43a0839d0 100644 --- a/solidago/src/solidago/primitives/datastructure/nested_dict.py +++ b/solidago/src/solidago/primitives/datastructure/nested_dict.py @@ -117,6 +117,17 @@ def set(self, keys: Union[str, tuple, list], value: "OutputValue") -> None: def __setitem__(self, keys: Union[str, tuple, list], value: "OutputValue") -> None: self.set(keys, value) + def reorder_keys(self, key_names: list[str]) -> "NestedDict": + if not key_names or self.key_names == key_names: + return self + assert all({ key_name in key_names for key_name in self.key_names }), (key_names, self.key_names) + key_names += [ key_name for key_name in self.key_names if key_name not in key_names ] + new2self_index = { i: self.key_names.index(key_names[i]) for i in range(len(key_names)) } + result = type(self)(key_names=key_names) + for self_keys, value in self.__iter__(process=False): + result[ [self_keys[new2self_index[i]] for i in range(len(key_names))] ] = value + return result + @classmethod def load(cls, filename: str) -> "NestedDict": try: return cls(pd.read_csv(filename, keep_default_na=False)) diff --git a/solidago/src/solidago/primitives/optimize.py b/solidago/src/solidago/primitives/optimize.py index ac31e57c12..5f5a74dff3 100644 --- a/solidago/src/solidago/primitives/optimize.py +++ b/solidago/src/solidago/primitives/optimize.py @@ -7,7 +7,7 @@ All rights reserved. """ -from typing import Callable, Tuple, Literal +from typing import Callable, Tuple, Literal, Optional import numpy as np from numba import njit @@ -178,7 +178,7 @@ def coordinate_descent( update_coordinate_function: Callable[[Tuple, float], float], get_args: Callable[[int, np.ndarray], Tuple], initialization: np.ndarray, - updated_coordinates: list[int], + updated_coordinates: Optional[list[int]]=None, error: float = 1e-5, ): """Minimize a loss function with coordinate descent, @@ -201,7 +201,7 @@ def coordinate_descent( For well behaved losses, there is a convergence guarantee """ unchanged = set() - to_pick = updated_coordinates + to_pick = list() if updated_coordinates is None else updated_coordinates solution = initialization solution_len = len(solution) diff --git a/solidago/src/solidago/state/assessments/base.py b/solidago/src/solidago/state/assessments/base.py index da35611638..2e495a50b8 100644 --- a/solidago/src/solidago/state/assessments/base.py +++ b/solidago/src/solidago/state/assessments/base.py @@ -10,9 +10,11 @@ def __init__(self, *args, **kwargs): class Assessments(NestedDictOfRowLists): + row_cls: type=Assessment + def __init__(self, d: Optional[Union[NestedDictOfRowLists, dict, DataFrame]]=None, - key_names=["username", "entity_name"], + key_names=["username", "criterion", "entity_name"], save_filename="assessments.csv" ): super().__init__(d, key_names, save_filename) @@ -21,18 +23,8 @@ def default_value(self) -> list: return list() def process_stored_value(self, keys: list[str], stored_value: list[dict]) -> list[Assessment]: - return [Assessment(v) for v in stored_value] + return [self.row_cls(v) for v in stored_value] def get_evaluators(self, entity: Union[str, "Entity"]) -> set[str]: - return set(self[any, entity]) + return self[{ "entity_name": entity }].get_set("username") - def get_evaluators_by_criterion(self, entity: Union[str, "Entity"]) -> dict[str, set[str]]: - assessments = self[any, entity] - evaluators = dict() - for username, row_list in assessments: - for row in row_list: - criterion = row["criterion"] if "criterion" in row else "default" - if criterion not in evaluators: - evaluators[criterion] = set() - evaluators[criterion].add(username) - return evaluators diff --git a/solidago/src/solidago/state/comparisons/base.py b/solidago/src/solidago/state/comparisons/base.py index 76278103aa..738ce52757 100644 --- a/solidago/src/solidago/state/comparisons/base.py +++ b/solidago/src/solidago/state/comparisons/base.py @@ -10,9 +10,11 @@ def __init__(self, *args, **kwargs): class Comparisons(NestedDictOfRowLists): + row_cls: type=Comparison + def __init__(self, d: Optional[Union[NestedDictOfRowLists, dict, DataFrame]]=None, - key_names=["username", "left_name", "right_name"], + key_names=["username", "criterion", "left_name", "right_name"], save_filename="comparisons.csv" ): super().__init__(d, key_names, save_filename) @@ -21,26 +23,19 @@ def default_value(self) -> list: return list() def process_stored_value(self, keys: list[str], stored_value: list[dict]) -> list[Comparison]: - return [Comparison(v) for v in stored_value] + return [self.row_cls(v) for v in stored_value] def get_evaluators(self, entity: Union[str, "Entity"]) -> set[str]: - return self[any, entity, any].get_set("username") | self[any, any, entity].get_set("username") - - def get_evaluators_by_criterion(self, entity: Union[str, "Entity"]) -> dict[str, set[str]]: - evaluators = dict() - for comparisons in (self[any, entity, any], self[any, any, entity]): - for username, row_list in comparisons: - for row in row_list: - criterion = row["criterion"] if "criterion" in row else "default" - if criterion not in evaluators: - evaluators[criterion] = set() - evaluators[criterion].add(username) - return evaluators + evaluators = self[{ "left_name": entity }].get_set("username") + return evaluators | self[{ "right_name": entity }].get_set("username") def order_by_entities(self) -> "Comparisons": - result = Comparisons(key_names=["entity"]) + if "entity_name" in self.key_names: + key_names = ["entity_name"] + [ kn for kn in key_names if kn != ["entity_name"] ] + return self.reorder_keys(key_names) assert "left_name" in self.key_names and "right_name" in self.key_names, "" \ "Comparisons must have columns `left_name` and `right_name`" + result = Comparisons(key_names=["entity_name"]) left_key_index = self.key_names.index("left_name") right_key_index = self.key_names.index("right_name") for keys, row_list in self: diff --git a/solidago/src/solidago/state/models/base.py b/solidago/src/solidago/state/models/base.py index 846a747a20..2466d8888c 100644 --- a/solidago/src/solidago/state/models/base.py +++ b/solidago/src/solidago/state/models/base.py @@ -54,7 +54,7 @@ def dfs_load(cls, d: dict[str, Any], loaded_dfs: Optional[dict[str, DataFrame]]= @classmethod def args_load(cls, d: dict[str, Any], dfs: dict[str, DataFrame], depth: int) -> dict: - return dict() + return d["args"] if "args" in d else dict() @classmethod def load(cls, d: dict, dfs: Optional[dict[str, DataFrame]]=None, depth: int=0) -> "ScoringModel": @@ -66,6 +66,9 @@ def load(cls, d: dict, dfs: Optional[dict[str, DataFrame]]=None, depth: int=0) - args["parent"] = getattr(models, base_cls).load(base_d, dfs, depth + 1) return cls(**args) + def args_save(self) -> dict: + return dict() + def save(self, filename_root: Optional[str]=None, depth: int=0, json_dump: bool=False) -> tuple[str, dict]: """ save must be given a filename_root (typically without extension), as multiple csv files may be saved, with a name derived from the filename_root @@ -77,6 +80,9 @@ def save(self, filename_root: Optional[str]=None, depth: int=0, json_dump: bool= saved_dict = dict() if not isinstance(self, BaseModel): saved_dict["parent"] = self.parent.save(depth=depth + 1) + args = self.args_save() + if args: + saved_dict["args"] = args for df_name, df in dfs.items(): save_filename = f"{filename_root}_{df_name}.csv" df.to_csv(save_filename, index=False) @@ -130,3 +136,7 @@ class BaseModel(ScoringModel): @property def parent(self) -> ScoringModel: raise ValueError(f"{type(self)} is a BaseModel and thus has no parent") + + @abstractmethod + def to_direct(self) -> "DirectScoring": + raise NotImplemented diff --git a/solidago/src/solidago/state/models/direct.py b/solidago/src/solidago/state/models/direct.py index 8d88256b03..c3e7dba6c2 100644 --- a/solidago/src/solidago/state/models/direct.py +++ b/solidago/src/solidago/state/models/direct.py @@ -34,3 +34,6 @@ def args_load(cls, d: dict[str, Any], dfs: dict[str, DataFrame], depth: int) -> def to_df(self, depth: int=0): return NestedDictOfTuples.to_df(self).assign(depth=depth) + + def to_direct(self) -> "DirectScoring": + return self diff --git a/solidago/src/solidago/state/models/post_processed.py b/solidago/src/solidago/state/models/post_processed.py index c24be84eb1..62e3f3585f 100644 --- a/solidago/src/solidago/state/models/post_processed.py +++ b/solidago/src/solidago/state/models/post_processed.py @@ -35,12 +35,16 @@ def post_process(self, score: Union[Score, MultiScore]) -> Union[Score, MultiSco class SquashedModel(PostProcessedModel): - def __init__(self, parent: ScoringModel): + def __init__(self, parent: ScoringModel, self.max_score: float=100.): super().__init__(parent) + self.max_score = max_score def post_process_fn(self, x: float) -> float: - return 100 * x / sqrt(1+x**2) + return self.max_score * x / sqrt(1+x**2) def save(self, directory: Union[Path, str], filename: Optional[str], depth: int=0 ) -> tuple[str, Union[dict, str, tuple, list]]: parent_instructions = self.parent.save(directory, depth) - return [type(self).__name__, { "parent": parent_instructions }] + return type(self).__name__, { + "parent": parent_instructions, + "args": { "max_score": self.max_score }, + } diff --git a/solidago/src/solidago/state/models/scaled.py b/solidago/src/solidago/state/models/scaled.py index 48f699b3ee..6700e6eb9c 100644 --- a/solidago/src/solidago/state/models/scaled.py +++ b/solidago/src/solidago/state/models/scaled.py @@ -8,7 +8,11 @@ class ScaledModel(ScoringModel): - def __init__(self, parent: ScoringModel, multiplicator: Score, translation: Score): + def __init__(self, + parent: ScoringModel, + multiplicator: Score=Score(1, 0, 0), + translation: Score=Score(0, 0, 0) + ): super().__init__() self.parent = parent self.multiplicator = multiplicator diff --git a/solidago/tests/load_save/test_tiny_tournesol.py b/solidago/tests/load_save/test_tiny_tournesol.py index a75828a9aa..887fb8734b 100644 --- a/solidago/tests/load_save/test_tiny_tournesol.py +++ b/solidago/tests/load_save/test_tiny_tournesol.py @@ -15,7 +15,7 @@ def test_import(): assert len(t.assessments) == 0 assert len(t.comparisons) == 2268 assert len(t.comparisons["amatissart"]) == 19 - assert t.comparisons[any, "Tt5AwEU_BiM", any].get_set("username") == {'amatissart', 'biscuissec'} + assert t.comparisons[any, any, "Tt5AwEU_BiM", any].get_set("username") == {'amatissart', 'biscuissec'} assert t.comparisons.get_evaluators("N8G-KGqn2Lg") == {'amatissart'} assert t.voting_rights["Tit0uan", "xMxo9pIC0GA"]["largely_recommended"] == 0.86 assert len(t.voting_rights["Tit0uan"]) == 3 @@ -42,7 +42,7 @@ def test_reimport(): assert len(t.assessments) == 0 assert len(t.comparisons) == 2268 assert len(t.comparisons["amatissart"]) == 19 - assert t.comparisons[any, "Tt5AwEU_BiM", any].get_set("username") == {'amatissart', 'biscuissec'} + assert t.comparisons[any, any, "Tt5AwEU_BiM", any].get_set("username") == {'amatissart', 'biscuissec'} assert t.comparisons.get_evaluators("N8G-KGqn2Lg") == {'amatissart'} assert t.voting_rights["Tit0uan", "xMxo9pIC0GA"]["largely_recommended"] == 0.86 assert len(t.voting_rights["Tit0uan"]) == 3 diff --git a/solidago/tests/save_tiny_tournesol/comparisons.csv b/solidago/tests/save_tiny_tournesol/comparisons.csv index 25b49b7f64..08deaedf59 100644 --- a/solidago/tests/save_tiny_tournesol/comparisons.csv +++ b/solidago/tests/save_tiny_tournesol/comparisons.csv @@ -1,2269 +1,2269 @@ -username,left_name,right_name,criterion,comparison,comparison_max,week_date,week_number -aidjango,2Z9p_I3hhUc,fQEiyUj_Dn0,importance,5,10,2021-01-11,0 -aidjango,2Z9p_I3hhUc,fQEiyUj_Dn0,entertaining_relaxing,-1,10,2021-01-11,0 -aidjango,2Z9p_I3hhUc,fQEiyUj_Dn0,largely_recommended,7,10,2021-01-11,0 -aidjango,2Z9p_I3hhUc,EGs5kYYw6d8,largely_recommended,-1,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,EGs5kYYw6d8,entertaining_relaxing,3,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,EGs5kYYw6d8,importance,-3,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,YMDJA4UvXLA,importance,-2,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,YMDJA4UvXLA,entertaining_relaxing,4,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,YMDJA4UvXLA,largely_recommended,0,10,2021-02-01,3 -aidjango,2Z9p_I3hhUc,wcfY44oh70Q,entertaining_relaxing,3,10,2021-03-29,11 -aidjango,2Z9p_I3hhUc,wcfY44oh70Q,largely_recommended,8,10,2021-03-29,11 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-aidjango,V6ChTqII-Yk,bL_8xKAyP_U,entertaining_relaxing,-6,10,2022-09-12,87 -aidjango,V6ChTqII-Yk,u3QnT73jE2U,entertaining_relaxing,-8,10,2022-09-12,87 -aidjango,V6ChTqII-Yk,u3QnT73jE2U,largely_recommended,-5,10,2022-09-12,87 -aidjango,V6ChTqII-Yk,u3QnT73jE2U,importance,-5,10,2022-09-12,87 -aidjango,V6ChTqII-Yk,OOVGnCbok34,largely_recommended,-3,10,2023-01-23,106 -aidjango,V6ChTqII-Yk,3mbBES5PyOk,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,V6ChTqII-Yk,3mbBES5PyOk,importance,-2,10,2023-01-23,106 -aidjango,V6ChTqII-Yk,3mbBES5PyOk,largely_recommended,-2,10,2023-01-23,106 -aidjango,V6ChTqII-Yk,3q-7Tam2cuc,largely_recommended,-2,10,2023-01-30,107 -aidjango,V6ChTqII-Yk,lC5lsemxaJo,largely_recommended,-3,10,2023-05-29,124 -aidjango,V6ChTqII-Yk,lC5lsemxaJo,importance,-3,10,2023-05-29,124 -aidjango,V6ChTqII-Yk,lC5lsemxaJo,entertaining_relaxing,3,10,2023-05-29,124 -aidjango,JuwDiKWEBgY,V6ChTqII-Yk,largely_recommended,3,10,2022-09-12,87 -aidjango,JuwDiKWEBgY,V6ChTqII-Yk,importance,-2,10,2022-09-12,87 -aidjango,JuwDiKWEBgY,V6ChTqII-Yk,entertaining_relaxing,4,10,2022-09-12,87 -aidjango,BDQX_Whx--E,ZzH-bAY6KGI,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,BDQX_Whx--E,ZzH-bAY6KGI,importance,0,10,2022-10-24,93 -aidjango,BDQX_Whx--E,ZzH-bAY6KGI,largely_recommended,0,10,2022-10-24,93 -aidjango,BDQX_Whx--E,rFGjqet5o2c,importance,0,10,2022-10-24,93 -aidjango,BDQX_Whx--E,rFGjqet5o2c,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,BDQX_Whx--E,rFGjqet5o2c,largely_recommended,0,10,2022-10-24,93 -aidjango,2wXjSyoWmeg,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,2wXjSyoWmeg,BDQX_Whx--E,importance,0,10,2022-10-24,93 -aidjango,2wXjSyoWmeg,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -aidjango,IYblisCkLiw,BDQX_Whx--E,importance,0,10,2022-10-24,93 -aidjango,IYblisCkLiw,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,IYblisCkLiw,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -aidjango,J5LodnKnLYU,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -aidjango,J5LodnKnLYU,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,J5LodnKnLYU,BDQX_Whx--E,importance,0,10,2022-10-24,93 -aidjango,rvskMHn0sqQ,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -aidjango,rvskMHn0sqQ,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -aidjango,rvskMHn0sqQ,BDQX_Whx--E,importance,0,10,2022-10-24,93 -aidjango,ju6hC1YF5TM,NxvQPzrg2Wg,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,NxvQPzrg2Wg,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,NxvQPzrg2Wg,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,VY2yv3zMOsI,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,VY2yv3zMOsI,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,VY2yv3zMOsI,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,eNvboEAaMyE,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,eNvboEAaMyE,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,eNvboEAaMyE,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,j7h75zxDEW8,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,j7h75zxDEW8,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,j7h75zxDEW8,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,ja6HqVej_yw,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,ja6HqVej_yw,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,ja6HqVej_yw,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,SKmgDiDPblA,importance,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,SKmgDiDPblA,largely_recommended,0,10,2022-11-14,96 -aidjango,ju6hC1YF5TM,SKmgDiDPblA,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,y6f3dwxexZM,ju6hC1YF5TM,largely_recommended,0,10,2022-11-14,96 -aidjango,y6f3dwxexZM,ju6hC1YF5TM,importance,0,10,2022-11-14,96 -aidjango,y6f3dwxexZM,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-11-14,96 -aidjango,oOzYpKi99z4,xeMbGBw7j8g,entertaining_relaxing,2,10,2022-11-21,97 -aidjango,oOzYpKi99z4,xeMbGBw7j8g,largely_recommended,2,10,2022-11-21,97 -aidjango,oOzYpKi99z4,xeMbGBw7j8g,importance,1,10,2022-11-21,97 -aidjango,46QRfChKDgg,xaQJbozY_Is,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,xaQJbozY_Is,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,xaQJbozY_Is,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,hCQ_qvxcf_o,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,hCQ_qvxcf_o,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,hCQ_qvxcf_o,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,YW3rHvMh5AE,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,YW3rHvMh5AE,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,YW3rHvMh5AE,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,9gPv4qzzb9Q,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,9gPv4qzzb9Q,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,9gPv4qzzb9Q,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,u148ZVqBBgY,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,u148ZVqBBgY,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,u148ZVqBBgY,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,QT-oDKHn-Fo,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,QT-oDKHn-Fo,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,QT-oDKHn-Fo,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,rd6Z0HQenuM,largely_recommended,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,rd6Z0HQenuM,importance,0,10,2022-11-28,98 -aidjango,46QRfChKDgg,rd6Z0HQenuM,entertaining_relaxing,0,10,2022-11-28,98 -aidjango,uljTEmmCh_E,d35JQvaEen0,importance,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,d35JQvaEen0,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,d35JQvaEen0,largely_recommended,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,JXeJANDKwDc,largely_recommended,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,JXeJANDKwDc,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,JXeJANDKwDc,importance,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,K9UE2WD6nu8,largely_recommended,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,K9UE2WD6nu8,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,K9UE2WD6nu8,importance,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,w9J6D4r30HY,largely_recommended,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,w9J6D4r30HY,importance,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,w9J6D4r30HY,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,7WGaMAb-ivs,importance,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,7WGaMAb-ivs,entertaining_relaxing,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,7WGaMAb-ivs,largely_recommended,0,10,2023-01-23,106 -aidjango,uljTEmmCh_E,uYYRAPBbr_w,entertaining_relaxing,0,10,2023-02-27,111 -aidjango,uljTEmmCh_E,uYYRAPBbr_w,importance,0,10,2023-02-27,111 -aidjango,uljTEmmCh_E,uYYRAPBbr_w,largely_recommended,0,10,2023-02-27,111 -aidjango,D9wrQj15ZA8,xwclx5F5Wfo,largely_recommended,4,10,2023-03-06,112 -aidjango,D9wrQj15ZA8,pP44EPBMb8A,largely_recommended,-9,10,2023-03-13,113 -aidjango,D9wrQj15ZA8,MxBpCAy0tqE,largely_recommended,-5,10,2023-03-13,113 -aidjango,D9wrQj15ZA8,MxBpCAy0tqE,entertaining_relaxing,8,10,2023-03-13,113 -aidjango,D9wrQj15ZA8,MxBpCAy0tqE,importance,-5,10,2023-03-13,113 -aidjango,GFqwpyfc0C0,q4xZArgOIWc,largely_recommended,-5,10,2023-03-06,112 -aidjango,GFqwpyfc0C0,q4xZArgOIWc,importance,-6,10,2023-03-06,112 -aidjango,GFqwpyfc0C0,q4xZArgOIWc,entertaining_relaxing,0,10,2023-03-06,112 -aidjango,hqBSYXMldh0,q4xZArgOIWc,importance,-3,10,2023-03-06,112 -aidjango,hqBSYXMldh0,q4xZArgOIWc,largely_recommended,-3,10,2023-03-06,112 -aidjango,hqBSYXMldh0,q4xZArgOIWc,entertaining_relaxing,-4,10,2023-03-06,112 -aidjango,q4xZArgOIWc,6-hQiPcHhFc,entertaining_relaxing,2,10,2023-03-13,113 -aidjango,q4xZArgOIWc,6-hQiPcHhFc,importance,4,10,2023-03-13,113 -aidjango,q4xZArgOIWc,6-hQiPcHhFc,largely_recommended,5,10,2023-03-13,113 -aidjango,q4xZArgOIWc,Fi6xY1YCTgM,largely_recommended,2,10,2023-03-13,113 -aidjango,q4xZArgOIWc,Fi6xY1YCTgM,importance,3,10,2023-03-13,113 -aidjango,q4xZArgOIWc,Fi6xY1YCTgM,entertaining_relaxing,-2,10,2023-03-13,113 -aidjango,NkJden7BJzc,D9wrQj15ZA8,largely_recommended,-3,10,2023-03-13,113 -aidjango,NkJden7BJzc,D9wrQj15ZA8,importance,0,10,2023-03-13,113 -aidjango,NkJden7BJzc,D9wrQj15ZA8,entertaining_relaxing,-2,10,2023-03-13,113 -aidjango,QcJgK4xEXbs,IqfUaWIC1Ww,largely_recommended,3,10,2023-06-26,128 -aidjango,QcJgK4xEXbs,895xdkeVJ3k,importance,4,10,2023-06-26,128 -aidjango,QcJgK4xEXbs,895xdkeVJ3k,largely_recommended,3,10,2023-06-26,128 -aidjango,QcJgK4xEXbs,895xdkeVJ3k,entertaining_relaxing,-2,10,2023-06-26,128 -aidjango,QcJgK4xEXbs,NOCsdhzo6Jg,largely_recommended,-3,10,2023-07-03,129 -aidjango,QcJgK4xEXbs,4GDLaYrMCFo,largely_recommended,5,10,2023-07-03,129 -aidjango,_1uN7o1PpZo,ymcBC7MFRIk,entertaining_relaxing,0,10,2023-07-03,129 -aidjango,_1uN7o1PpZo,ymcBC7MFRIk,importance,9,10,2023-07-03,129 -aidjango,_1uN7o1PpZo,ymcBC7MFRIk,largely_recommended,9,10,2023-07-03,129 -aidjango,_1uN7o1PpZo,It1dTn8zWcE,largely_recommended,-9,10,2023-07-03,129 -aidjango,_4ICxLCJczI,_1uN7o1PpZo,entertaining_relaxing,1,10,2023-07-03,129 -aidjango,_4ICxLCJczI,_1uN7o1PpZo,largely_recommended,-8,10,2023-07-03,129 -aidjango,_4ICxLCJczI,_1uN7o1PpZo,importance,-9,10,2023-07-03,129 -aidjango,aKoiSPDxsso,_1uN7o1PpZo,entertaining_relaxing,0,10,2023-07-03,129 -aidjango,aKoiSPDxsso,_1uN7o1PpZo,importance,-8,10,2023-07-03,129 -aidjango,aKoiSPDxsso,_1uN7o1PpZo,largely_recommended,-8,10,2023-07-03,129 -aidjango,LXVa9HCHa_M,_ElagKA5T44,largely_recommended,4,10,2023-11-27,150 -aidjango,LXVa9HCHa_M,TGWcKOpfuR8,entertaining_relaxing,-10,10,2023-11-27,150 -aidjango,LXVa9HCHa_M,TGWcKOpfuR8,importance,-10,10,2023-11-27,150 -aidjango,LXVa9HCHa_M,TGWcKOpfuR8,largely_recommended,-10,10,2023-11-27,150 -aidjango,MmOYmPM7OFE,1zqmcV1O4fU,largely_recommended,-3,10,2024-05-06,173 -aidjango,MmOYmPM7OFE,J98vK1YUKQ4,largely_recommended,2,10,2024-05-06,173 -aidjango,LIWcjcdzhDk,MmOYmPM7OFE,largely_recommended,-3,10,2024-05-06,173 -aidjango,zGH5sxyoVZU,MmOYmPM7OFE,largely_recommended,-1,10,2024-06-03,177 -aidjango,zGH5sxyoVZU,MmOYmPM7OFE,entertaining_relaxing,-5,10,2024-06-03,177 -aidjango,ZkMP6YD52L8,wtJwVZGuiOY,entertaining_relaxing,-4,10,2024-06-17,179 -aidjango,ZkMP6YD52L8,wtJwVZGuiOY,largely_recommended,3,10,2024-06-17,179 -aidjango,ZkMP6YD52L8,EjJLlhLnliQ,largely_recommended,-2,10,2024-06-17,179 -aidjango,ZkMP6YD52L8,EjJLlhLnliQ,entertaining_relaxing,-1,10,2024-06-17,179 -aidjango,ZkMP6YD52L8,V_Pug96vCwc,largely_recommended,-3,10,2024-09-02,190 -aidjango,ZkMP6YD52L8,V_Pug96vCwc,entertaining_relaxing,-5,10,2024-09-02,190 -aidjango,ZkMP6YD52L8,hNMRSUFuHPg,largely_recommended,-2,10,2024-09-02,190 -aidjango,ZkMP6YD52L8,hNMRSUFuHPg,entertaining_relaxing,-5,10,2024-09-02,190 -aidjango,jCHBfknkwVE,EjJLlhLnliQ,largely_recommended,-3,10,2024-06-17,179 -aidjango,jCHBfknkwVE,EjJLlhLnliQ,entertaining_relaxing,2,10,2024-06-17,179 -aidjango,FQC8il4hoGw,EjJLlhLnliQ,entertaining_relaxing,4,10,2024-06-24,180 -aidjango,FQC8il4hoGw,EjJLlhLnliQ,largely_recommended,-5,10,2024-06-24,180 -aidjango,JO8Gv4wv0Xc,EjJLlhLnliQ,largely_recommended,-6,10,2024-06-24,180 -aidjango,JO8Gv4wv0Xc,EjJLlhLnliQ,entertaining_relaxing,3,10,2024-06-24,180 -aidjango,au7YkV81buI,eVtc1EGFmR8,largely_recommended,3,10,2024-09-02,190 -aidjango,au7YkV81buI,eVtc1EGFmR8,entertaining_relaxing,5,10,2024-09-02,190 -aidjango,au7YkV81buI,T8YVfcDYTSY,entertaining_relaxing,3,10,2024-09-02,190 -aidjango,au7YkV81buI,T8YVfcDYTSY,largely_recommended,2,10,2024-09-02,190 -aidjango,zt4zEM6q4Ic,au7YkV81buI,entertaining_relaxing,0,10,2024-09-30,194 -aidjango,zt4zEM6q4Ic,au7YkV81buI,largely_recommended,-3,10,2024-09-30,194 -aidjango,rJE2qkP0Gk4,au7YkV81buI,entertaining_relaxing,-5,10,2024-10-14,196 -aidjango,rJE2qkP0Gk4,au7YkV81buI,largely_recommended,-4,10,2024-10-14,196 -amatissart,Tt5AwEU_BiM,9KOZUw_Ah8w,largely_recommended,-3,10,2022-12-19,101 -amatissart,Tt5AwEU_BiM,UMqLDhl8PXw,largely_recommended,3,10,2022-12-19,101 -amatissart,eBOgUF5Xex8,Tt5AwEU_BiM,largely_recommended,-1,10,2022-12-19,101 -amatissart,HcFvegnQpPo,Tt5AwEU_BiM,largely_recommended,-2,10,2022-12-19,101 -amatissart,NCsMtn8XgT0,Tt5AwEU_BiM,largely_recommended,1,10,2022-12-19,101 -amatissart,AzSaNhoB2JI,Tt5AwEU_BiM,largely_recommended,4,10,2022-12-19,101 -amatissart,QZJy_CIgABw,tg--L9TKL0I,largely_recommended,3,10,2022-12-26,102 -amatissart,QZJy_CIgABw,Eh7l4Gvx054,largely_recommended,4,10,2023-01-16,105 -amatissart,h7EAfUeSBSQ,QZJy_CIgABw,largely_recommended,-1,10,2022-12-26,102 -amatissart,VztEcSYXQr0,QZJy_CIgABw,largely_recommended,1,10,2022-12-26,102 -amatissart,kR3JaROyKuA,VNwATZ-07nk,largely_recommended,-5,10,2023-08-28,137 -amatissart,zyhNeM2H13g,VNwATZ-07nk,largely_recommended,-3,10,2023-11-06,147 -amatissart,eymKly8CoUI,VNwATZ-07nk,entertaining_relaxing,-5,10,2023-11-27,150 -amatissart,eymKly8CoUI,VNwATZ-07nk,largely_recommended,-5,10,2023-11-27,150 -amatissart,N8G-KGqn2Lg,jacTrjXVRkc,largely_recommended,0,2,2024-12-09,204 -amatissart,N8G-KGqn2Lg,FQaLL_qX8Ds,largely_recommended,-1,2,2024-12-09,204 -amatissart,N8G-KGqn2Lg,LcI6F_GPwfE,largely_recommended,-2,2,2024-12-09,204 -amatissart,N8G-KGqn2Lg,ikRLGSn2fH4,largely_recommended,0,2,2024-12-09,204 -amatissart,N8G-KGqn2Lg,_I7tXtN7Zhw,largely_recommended,-2,2,2024-12-09,204 -Antarctus,xeMbGBw7j8g,auKJTuT3LV4,entertaining_relaxing,-5,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,auKJTuT3LV4,importance,3,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,auKJTuT3LV4,largely_recommended,2,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gpBqw2sTD08,importance,5,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gpBqw2sTD08,entertaining_relaxing,10,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gpBqw2sTD08,largely_recommended,7,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gV2v0w3EXoA,entertaining_relaxing,7,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gV2v0w3EXoA,importance,-1,10,2024-07-29,185 -Antarctus,xeMbGBw7j8g,gV2v0w3EXoA,largely_recommended,1,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,WP6T4MH0Dn4,largely_recommended,3,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,WP6T4MH0Dn4,importance,-1,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,WP6T4MH0Dn4,entertaining_relaxing,4,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,0yQOGAS17uw,largely_recommended,2,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,0yQOGAS17uw,entertaining_relaxing,-3,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,0yQOGAS17uw,importance,4,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,Tv40uWRKJks,entertaining_relaxing,4,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,Tv40uWRKJks,importance,-4,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,Tv40uWRKJks,largely_recommended,6,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,xeMbGBw7j8g,importance,-2,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,xeMbGBw7j8g,entertaining_relaxing,4,10,2024-07-29,185 -Antarctus,E1Dn3F7Ili8,xeMbGBw7j8g,largely_recommended,3,10,2024-07-29,185 -Antarctus,CGRtyxEpoGg,E1Dn3F7Ili8,largely_recommended,-4,10,2024-07-29,185 -Antarctus,CGRtyxEpoGg,E1Dn3F7Ili8,entertaining_relaxing,5,10,2024-07-29,185 -Antarctus,CGRtyxEpoGg,E1Dn3F7Ili8,importance,-4,10,2024-07-29,185 -Antarctus,segcFv9UcCg,xeMbGBw7j8g,entertaining_relaxing,3,10,2024-07-29,185 -Antarctus,segcFv9UcCg,xeMbGBw7j8g,largely_recommended,-2,10,2024-07-29,185 -Antarctus,segcFv9UcCg,xeMbGBw7j8g,importance,-7,10,2024-07-29,185 -Antarctus,jbdVG7lXehU,u3iJKE3PdEM,importance,-4,10,2024-09-30,194 -Antarctus,jbdVG7lXehU,u3iJKE3PdEM,entertaining_relaxing,2,10,2024-09-30,194 -Antarctus,jbdVG7lXehU,u3iJKE3PdEM,largely_recommended,-4,10,2024-09-30,194 -Antarctus,u3iJKE3PdEM,5iPH-br_eJQ,largely_recommended,6,10,2024-09-30,194 -Antarctus,u3iJKE3PdEM,5iPH-br_eJQ,importance,8,10,2024-09-30,194 -Antarctus,u3iJKE3PdEM,5iPH-br_eJQ,entertaining_relaxing,7,10,2024-09-30,194 -Antarctus,u3iJKE3PdEM,N_ayq66t77U,largely_recommended,6,10,2024-10-07,195 -Antarctus,u3iJKE3PdEM,N_ayq66t77U,importance,6,10,2024-10-07,195 -Antarctus,u3iJKE3PdEM,N_ayq66t77U,entertaining_relaxing,8,10,2024-10-07,195 -Antarctus,2cvj2-Vh8Uc,E1Dn3F7Ili8,largely_recommended,-4,10,2024-10-07,195 -Antarctus,2cvj2-Vh8Uc,E1Dn3F7Ili8,entertaining_relaxing,-2,10,2024-10-07,195 -Antarctus,2cvj2-Vh8Uc,E1Dn3F7Ili8,importance,-6,10,2024-10-07,195 -Antarctus,WazrsWXi44k,u3iJKE3PdEM,entertaining_relaxing,-4,10,2024-10-07,195 -Antarctus,WazrsWXi44k,u3iJKE3PdEM,importance,-7,10,2024-10-07,195 -Antarctus,WazrsWXi44k,u3iJKE3PdEM,largely_recommended,-3,10,2024-10-07,195 -Antarctus,ZP7T6WAK3Ow,eMn43As24Bo,entertaining_relaxing,-2,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,eMn43As24Bo,importance,-6,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,eMn43As24Bo,largely_recommended,-3,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,_rBPwu2uS-w,importance,-7,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,_rBPwu2uS-w,entertaining_relaxing,-2,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,_rBPwu2uS-w,largely_recommended,0,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,UjtOGPJ0URM,importance,-5,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,UjtOGPJ0URM,largely_recommended,0,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,UjtOGPJ0URM,entertaining_relaxing,5,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,j2zv4jlo2Nw,largely_recommended,1,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,j2zv4jlo2Nw,importance,-4,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,j2zv4jlo2Nw,entertaining_relaxing,-5,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,u3iJKE3PdEM,largely_recommended,-5,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,u3iJKE3PdEM,importance,-8,10,2024-10-14,196 -Antarctus,ZP7T6WAK3Ow,u3iJKE3PdEM,entertaining_relaxing,-2,10,2024-10-14,196 -Antarctus,rJE2qkP0Gk4,xeMbGBw7j8g,entertaining_relaxing,-5,10,2024-10-21,197 -Antarctus,rJE2qkP0Gk4,xeMbGBw7j8g,importance,4,10,2024-10-21,197 -Antarctus,rJE2qkP0Gk4,xeMbGBw7j8g,largely_recommended,0,10,2024-10-21,197 -biscuissec,XRk2VeL0icU,FGR9VUcvgY8,largely_recommended,1,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,FGR9VUcvgY8,importance,4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,FGR9VUcvgY8,entertaining_relaxing,4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,VKsekCHBuHI,importance,2,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,VKsekCHBuHI,entertaining_relaxing,-1,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,VKsekCHBuHI,largely_recommended,1,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,oakWgLqCwUc,largely_recommended,1,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,oakWgLqCwUc,entertaining_relaxing,4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,oakWgLqCwUc,importance,4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,qp5HPksrhNE,importance,-4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,qp5HPksrhNE,entertaining_relaxing,-2,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,qp5HPksrhNE,largely_recommended,-3,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,x3rptRn6GeA,largely_recommended,-3,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,x3rptRn6GeA,importance,-4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,x3rptRn6GeA,entertaining_relaxing,-2,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,2__Dd_KXuuU,largely_recommended,1,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,2__Dd_KXuuU,entertaining_relaxing,-4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,2__Dd_KXuuU,importance,4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,CG8yN4A4fuM,largely_recommended,-4,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,CG8yN4A4fuM,entertaining_relaxing,-2,10,2021-12-06,47 -biscuissec,XRk2VeL0icU,CG8yN4A4fuM,importance,0,10,2021-12-06,47 -biscuissec,PgUN1uy8PYE,XREXROcadQM,importance,4,10,2021-12-13,48 -biscuissec,PgUN1uy8PYE,XREXROcadQM,entertaining_relaxing,-1,10,2021-12-13,48 -biscuissec,PgUN1uy8PYE,XREXROcadQM,largely_recommended,2,10,2021-12-13,48 -biscuissec,OlmXLuz2_mc,fksKuXhvWX4,largely_recommended,2,10,2022-02-07,56 -biscuissec,OlmXLuz2_mc,fksKuXhvWX4,importance,0,10,2022-02-07,56 -biscuissec,OlmXLuz2_mc,fksKuXhvWX4,entertaining_relaxing,2,10,2022-02-07,56 -biscuissec,FhjOz4ofy4g,fksKuXhvWX4,largely_recommended,6,10,2022-02-07,56 -biscuissec,FhjOz4ofy4g,fksKuXhvWX4,importance,6,10,2022-02-07,56 -biscuissec,FhjOz4ofy4g,fksKuXhvWX4,entertaining_relaxing,0,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,DV1x_9z_LMc,largely_recommended,-6,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,DV1x_9z_LMc,importance,-4,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,DV1x_9z_LMc,entertaining_relaxing,-6,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,vN2hmYyQo3o,largely_recommended,-10,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,vN2hmYyQo3o,importance,-10,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,vN2hmYyQo3o,entertaining_relaxing,-10,10,2022-02-07,56 -biscuissec,fksKuXhvWX4,SCYMx75Ao8A,entertaining_relaxing,-3,10,2022-02-14,57 -biscuissec,fksKuXhvWX4,SCYMx75Ao8A,largely_recommended,-2,10,2022-02-14,57 -biscuissec,fksKuXhvWX4,SCYMx75Ao8A,importance,-3,10,2022-02-14,57 -biscuissec,yAtDuXaEtFI,fksKuXhvWX4,importance,-4,10,2022-02-14,57 -biscuissec,yAtDuXaEtFI,fksKuXhvWX4,entertaining_relaxing,6,10,2022-02-14,57 -biscuissec,yAtDuXaEtFI,fksKuXhvWX4,largely_recommended,0,10,2022-02-14,57 -biscuissec,VY2yv3zMOsI,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,VY2yv3zMOsI,ju6hC1YF5TM,importance,0,10,2022-08-01,81 -biscuissec,VY2yv3zMOsI,ju6hC1YF5TM,largely_recommended,0,10,2022-08-01,81 -biscuissec,y6f3dwxexZM,ju6hC1YF5TM,largely_recommended,0,10,2022-08-01,81 -biscuissec,y6f3dwxexZM,ju6hC1YF5TM,importance,0,10,2022-08-01,81 -biscuissec,y6f3dwxexZM,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,NxvQPzrg2Wg,ju6hC1YF5TM,importance,0,10,2022-08-01,81 -biscuissec,NxvQPzrg2Wg,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,NxvQPzrg2Wg,ju6hC1YF5TM,largely_recommended,0,10,2022-08-01,81 -biscuissec,SKmgDiDPblA,ju6hC1YF5TM,importance,0,10,2022-08-01,81 -biscuissec,SKmgDiDPblA,ju6hC1YF5TM,largely_recommended,0,10,2022-08-01,81 -biscuissec,SKmgDiDPblA,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,j7h75zxDEW8,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,j7h75zxDEW8,ju6hC1YF5TM,largely_recommended,0,10,2022-08-01,81 -biscuissec,j7h75zxDEW8,ju6hC1YF5TM,importance,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,nJkJT1uiFB8,importance,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,nJkJT1uiFB8,largely_recommended,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,nJkJT1uiFB8,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,5IpAsztfBBA,importance,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,5IpAsztfBBA,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,5IpAsztfBBA,largely_recommended,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,oakWgLqCwUc,importance,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,oakWgLqCwUc,largely_recommended,0,10,2022-08-01,81 -biscuissec,ju6hC1YF5TM,oakWgLqCwUc,entertaining_relaxing,0,10,2022-08-01,81 -biscuissec,ja6HqVej_yw,ju6hC1YF5TM,largely_recommended,0,10,2022-08-15,83 -biscuissec,ja6HqVej_yw,ju6hC1YF5TM,importance,0,10,2022-08-15,83 -biscuissec,ja6HqVej_yw,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-15,83 -biscuissec,TrMSt1xMRWQ,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-15,83 -biscuissec,TrMSt1xMRWQ,ju6hC1YF5TM,importance,0,10,2022-08-15,83 -biscuissec,TrMSt1xMRWQ,ju6hC1YF5TM,largely_recommended,0,10,2022-08-15,83 -biscuissec,eNvboEAaMyE,ju6hC1YF5TM,largely_recommended,0,10,2022-08-15,83 -biscuissec,eNvboEAaMyE,ju6hC1YF5TM,entertaining_relaxing,0,10,2022-08-15,83 -biscuissec,eNvboEAaMyE,ju6hC1YF5TM,importance,0,10,2022-08-15,83 -biscuissec,Z6tKCJhlN9U,Vp_GDh1yQ-4,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,Vp_GDh1yQ-4,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,Vp_GDh1yQ-4,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,OIsPAA9T7m4,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,OIsPAA9T7m4,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,OIsPAA9T7m4,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,Po4O-gwvuQY,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,Po4O-gwvuQY,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,Po4O-gwvuQY,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HPdHj7rqLyc,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HPdHj7rqLyc,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HPdHj7rqLyc,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,trg06GQ3VkU,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,trg06GQ3VkU,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,trg06GQ3VkU,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,DwqwRYe6fKA,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,DwqwRYe6fKA,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,DwqwRYe6fKA,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,yT01CAWDtGM,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,yT01CAWDtGM,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,yT01CAWDtGM,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,n3Xv_g3g-mA,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,n3Xv_g3g-mA,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,n3Xv_g3g-mA,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,I9hJ_Rux9y0,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,I9hJ_Rux9y0,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,I9hJ_Rux9y0,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HYuqC13LZ1Q,largely_recommended,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HYuqC13LZ1Q,importance,0,10,2022-09-05,86 -biscuissec,Z6tKCJhlN9U,HYuqC13LZ1Q,entertaining_relaxing,0,10,2022-09-05,86 -biscuissec,dnT_Fu3CLPw,V6ChTqII-Yk,largely_recommended,-3,10,2022-09-12,87 -biscuissec,dnT_Fu3CLPw,V6ChTqII-Yk,importance,-3,10,2022-09-12,87 -biscuissec,dnT_Fu3CLPw,V6ChTqII-Yk,entertaining_relaxing,6,10,2022-09-12,87 -biscuissec,baxj1kuaWJ8,V6ChTqII-Yk,importance,-3,10,2022-09-19,88 -biscuissec,baxj1kuaWJ8,V6ChTqII-Yk,entertaining_relaxing,7,10,2022-09-19,88 -biscuissec,baxj1kuaWJ8,V6ChTqII-Yk,largely_recommended,-3,10,2022-09-19,88 -biscuissec,c2VgEeq_V48,V6ChTqII-Yk,entertaining_relaxing,-2,10,2022-09-26,89 -biscuissec,c2VgEeq_V48,V6ChTqII-Yk,importance,0,10,2022-09-26,89 -biscuissec,c2VgEeq_V48,V6ChTqII-Yk,largely_recommended,-1,10,2022-09-26,89 -biscuissec,XulBKrrRC3k,V6ChTqII-Yk,largely_recommended,0,10,2022-10-03,90 -biscuissec,XulBKrrRC3k,V6ChTqII-Yk,entertaining_relaxing,-3,10,2022-10-03,90 -biscuissec,XulBKrrRC3k,V6ChTqII-Yk,importance,2,10,2022-10-03,90 -biscuissec,rvskMHn0sqQ,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,rvskMHn0sqQ,BDQX_Whx--E,importance,0,10,2022-10-10,91 -biscuissec,rvskMHn0sqQ,BDQX_Whx--E,largely_recommended,0,10,2022-10-10,91 -biscuissec,J5LodnKnLYU,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,J5LodnKnLYU,BDQX_Whx--E,importance,0,10,2022-10-10,91 -biscuissec,J5LodnKnLYU,BDQX_Whx--E,largely_recommended,0,10,2022-10-10,91 -biscuissec,2wXjSyoWmeg,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,2wXjSyoWmeg,BDQX_Whx--E,importance,0,10,2022-10-10,91 -biscuissec,2wXjSyoWmeg,BDQX_Whx--E,largely_recommended,0,10,2022-10-10,91 -biscuissec,GNmp_T2OWfk,BDQX_Whx--E,importance,0,10,2022-10-10,91 -biscuissec,GNmp_T2OWfk,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,GNmp_T2OWfk,BDQX_Whx--E,largely_recommended,0,10,2022-10-10,91 -biscuissec,IYblisCkLiw,BDQX_Whx--E,largely_recommended,0,10,2022-10-10,91 -biscuissec,IYblisCkLiw,BDQX_Whx--E,importance,0,10,2022-10-10,91 -biscuissec,IYblisCkLiw,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,KOZXFn3P_AE,largely_recommended,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,KOZXFn3P_AE,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,KOZXFn3P_AE,importance,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,rFGjqet5o2c,largely_recommended,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,rFGjqet5o2c,importance,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,rFGjqet5o2c,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,ZzH-bAY6KGI,largely_recommended,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,ZzH-bAY6KGI,importance,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,ZzH-bAY6KGI,entertaining_relaxing,0,10,2022-10-10,91 -biscuissec,BDQX_Whx--E,nJslrTT-Yhc,largely_recommended,-2,10,2022-10-31,94 -biscuissec,BDQX_Whx--E,nJslrTT-Yhc,importance,-1,10,2022-10-31,94 -biscuissec,BDQX_Whx--E,nJslrTT-Yhc,entertaining_relaxing,-6,10,2022-10-31,94 -biscuissec,BDQX_Whx--E,MqmSMunAtss,importance,0,10,2022-10-31,94 -biscuissec,BDQX_Whx--E,MqmSMunAtss,entertaining_relaxing,1,10,2022-10-31,94 -biscuissec,BDQX_Whx--E,MqmSMunAtss,largely_recommended,0,10,2022-10-31,94 -biscuissec,kxV8mkfzYrI,aIp-aa8F9EI,importance,10,10,2022-10-24,93 -biscuissec,kxV8mkfzYrI,aIp-aa8F9EI,entertaining_relaxing,8,10,2022-10-24,93 -biscuissec,kxV8mkfzYrI,aIp-aa8F9EI,largely_recommended,10,10,2022-10-24,93 -biscuissec,Tt5AwEU_BiM,iOlz5OBMr7A,largely_recommended,-7,10,2022-11-07,95 -biscuissec,Tt5AwEU_BiM,iOlz5OBMr7A,entertaining_relaxing,-3,10,2022-11-07,95 -biscuissec,Tt5AwEU_BiM,iOlz5OBMr7A,importance,-7,10,2022-11-07,95 -biscuissec,Tt5AwEU_BiM,cQcHghE856E,largely_recommended,3,10,2022-11-07,95 -biscuissec,Tt5AwEU_BiM,cQcHghE856E,importance,3,10,2022-11-07,95 -biscuissec,Tt5AwEU_BiM,cQcHghE856E,entertaining_relaxing,-2,10,2022-11-07,95 -biscuissec,vzJAvChiozY,Tt5AwEU_BiM,entertaining_relaxing,0,10,2022-11-14,96 -biscuissec,vzJAvChiozY,Tt5AwEU_BiM,largely_recommended,4,10,2022-11-14,96 -biscuissec,vzJAvChiozY,Tt5AwEU_BiM,importance,2,10,2022-11-14,96 -biscuissec,dAMXH2_dcvs,Tt5AwEU_BiM,largely_recommended,4,10,2022-11-21,97 -biscuissec,dAMXH2_dcvs,Tt5AwEU_BiM,importance,0,10,2022-11-21,97 -biscuissec,dAMXH2_dcvs,Tt5AwEU_BiM,entertaining_relaxing,6,10,2022-11-21,97 -biscuissec,46QRfChKDgg,xaQJbozY_Is,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,xaQJbozY_Is,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,xaQJbozY_Is,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,hCQ_qvxcf_o,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,hCQ_qvxcf_o,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,hCQ_qvxcf_o,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,YW3rHvMh5AE,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,YW3rHvMh5AE,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,YW3rHvMh5AE,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,9gPv4qzzb9Q,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,9gPv4qzzb9Q,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,9gPv4qzzb9Q,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,rd6Z0HQenuM,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,rd6Z0HQenuM,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,rd6Z0HQenuM,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,u148ZVqBBgY,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,u148ZVqBBgY,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,u148ZVqBBgY,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,QT-oDKHn-Fo,entertaining_relaxing,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,QT-oDKHn-Fo,largely_recommended,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,QT-oDKHn-Fo,importance,0,10,2022-11-28,98 -biscuissec,46QRfChKDgg,KJ04GQYWH28,largely_recommended,-10,10,2023-06-12,126 -biscuissec,46QRfChKDgg,KJ04GQYWH28,entertaining_relaxing,-10,10,2023-06-12,126 -biscuissec,46QRfChKDgg,KJ04GQYWH28,importance,-10,10,2023-06-12,126 -biscuissec,bL_8xKAyP_U,46QRfChKDgg,largely_recommended,-3,10,2022-11-28,98 -biscuissec,bL_8xKAyP_U,46QRfChKDgg,importance,-6,10,2022-11-28,98 -biscuissec,bL_8xKAyP_U,46QRfChKDgg,entertaining_relaxing,6,10,2022-11-28,98 -biscuissec,aIp-aa8F9EI,PkYXSCXMg_8,entertaining_relaxing,-10,10,2022-12-12,100 -biscuissec,aIp-aa8F9EI,PkYXSCXMg_8,importance,-10,10,2022-12-12,100 -biscuissec,aIp-aa8F9EI,PkYXSCXMg_8,largely_recommended,-10,10,2022-12-12,100 -biscuissec,JXeJANDKwDc,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -biscuissec,JXeJANDKwDc,uljTEmmCh_E,importance,0,10,2023-01-23,106 -biscuissec,JXeJANDKwDc,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,d35JQvaEen0,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -biscuissec,d35JQvaEen0,uljTEmmCh_E,importance,0,10,2023-01-23,106 -biscuissec,d35JQvaEen0,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,9BBqFZwBsgs,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,9BBqFZwBsgs,uljTEmmCh_E,importance,0,10,2023-01-23,106 -biscuissec,9BBqFZwBsgs,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -biscuissec,bAn5zcG8-HA,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -biscuissec,bAn5zcG8-HA,uljTEmmCh_E,importance,0,10,2023-01-23,106 -biscuissec,bAn5zcG8-HA,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,igtR3tsRkqk,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -biscuissec,igtR3tsRkqk,uljTEmmCh_E,entertaining_relaxing,-1,10,2023-01-23,106 -biscuissec,igtR3tsRkqk,uljTEmmCh_E,importance,-1,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,7WGaMAb-ivs,largely_recommended,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,7WGaMAb-ivs,importance,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,7WGaMAb-ivs,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,K9UE2WD6nu8,largely_recommended,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,K9UE2WD6nu8,importance,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,K9UE2WD6nu8,entertaining_relaxing,0,10,2023-01-23,106 -biscuissec,uljTEmmCh_E,ZoSlPBuZtO4,largely_recommended,0,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,ZoSlPBuZtO4,entertaining_relaxing,-4,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,ZoSlPBuZtO4,importance,2,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,6gjMfVcKA_o,largely_recommended,0,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,6gjMfVcKA_o,entertaining_relaxing,-6,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,6gjMfVcKA_o,importance,2,10,2023-02-13,109 -biscuissec,uljTEmmCh_E,uYYRAPBbr_w,largely_recommended,0,10,2023-02-20,110 -biscuissec,uljTEmmCh_E,uYYRAPBbr_w,importance,0,10,2023-02-20,110 -biscuissec,uljTEmmCh_E,uYYRAPBbr_w,entertaining_relaxing,0,10,2023-02-20,110 -biscuissec,uljTEmmCh_E,SgxGQ7-3u-I,entertaining_relaxing,-10,10,2023-02-27,111 -biscuissec,uljTEmmCh_E,SgxGQ7-3u-I,largely_recommended,-10,10,2023-02-27,111 -biscuissec,uljTEmmCh_E,SgxGQ7-3u-I,importance,-10,10,2023-02-27,111 -biscuissec,tRhfOtpYG2U,C_gMPaP8x5I,entertaining_relaxing,2,10,2023-03-06,112 -biscuissec,tRhfOtpYG2U,C_gMPaP8x5I,largely_recommended,1,10,2023-03-06,112 -biscuissec,tRhfOtpYG2U,C_gMPaP8x5I,importance,1,10,2023-03-06,112 -biscuissec,3DOcQRl9ASc,C_gMPaP8x5I,largely_recommended,0,10,2023-03-06,112 -biscuissec,3DOcQRl9ASc,C_gMPaP8x5I,entertaining_relaxing,-1,10,2023-03-06,112 -biscuissec,3DOcQRl9ASc,C_gMPaP8x5I,importance,0,10,2023-03-06,112 -biscuissec,JAdhaZqU_Fw,C_gMPaP8x5I,importance,4,10,2023-03-06,112 -biscuissec,JAdhaZqU_Fw,C_gMPaP8x5I,entertaining_relaxing,-7,10,2023-03-06,112 -biscuissec,JAdhaZqU_Fw,C_gMPaP8x5I,largely_recommended,3,10,2023-03-06,112 -biscuissec,C_gMPaP8x5I,V6x9bXTU0vY,entertaining_relaxing,-6,10,2023-03-06,112 -biscuissec,C_gMPaP8x5I,V6x9bXTU0vY,largely_recommended,-1,10,2023-03-06,112 -biscuissec,C_gMPaP8x5I,V6x9bXTU0vY,importance,1,10,2023-03-06,112 -biscuissec,xeMbGBw7j8g,8y67NFHpxwI,entertaining_relaxing,-4,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,8y67NFHpxwI,importance,-1,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,8y67NFHpxwI,largely_recommended,-1,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,X1dJGyjp2d0,largely_recommended,0,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,X1dJGyjp2d0,entertaining_relaxing,0,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,X1dJGyjp2d0,importance,0,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,9CO6M2HsoIA,largely_recommended,1,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,9CO6M2HsoIA,entertaining_relaxing,-2,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,9CO6M2HsoIA,importance,1,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,R2fjRbc9Sa0,largely_recommended,0,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,R2fjRbc9Sa0,entertaining_relaxing,-2,10,2023-03-20,114 -biscuissec,xeMbGBw7j8g,R2fjRbc9Sa0,importance,0,10,2023-03-20,114 -biscuissec,XKd_cq26Isk,ups_V_DwpV8,largely_recommended,-5,10,2023-05-15,122 -biscuissec,XKd_cq26Isk,ups_V_DwpV8,importance,-6,10,2023-05-15,122 -biscuissec,XKd_cq26Isk,ups_V_DwpV8,entertaining_relaxing,2,10,2023-05-15,122 -biscuissec,uFRbyyWRfCU,ups_V_DwpV8,entertaining_relaxing,0,10,2023-05-15,122 -biscuissec,uFRbyyWRfCU,ups_V_DwpV8,importance,0,10,2023-05-15,122 -biscuissec,uFRbyyWRfCU,ups_V_DwpV8,largely_recommended,0,10,2023-05-15,122 -biscuissec,KtjTrpejAnE,ups_V_DwpV8,largely_recommended,0,10,2023-05-15,122 -biscuissec,KtjTrpejAnE,ups_V_DwpV8,importance,0,10,2023-05-15,122 -biscuissec,KtjTrpejAnE,ups_V_DwpV8,entertaining_relaxing,0,10,2023-05-15,122 -biscuissec,Un67JkVy0xo,tyCaMQPLRIA,entertaining_relaxing,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,tyCaMQPLRIA,importance,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,tyCaMQPLRIA,largely_recommended,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,LivgDUP7cAs,importance,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,LivgDUP7cAs,entertaining_relaxing,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,LivgDUP7cAs,largely_recommended,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,Qf3fuHTxRXs,importance,1,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,Qf3fuHTxRXs,largely_recommended,0,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,Qf3fuHTxRXs,entertaining_relaxing,2,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,FZ0mIU8Ih64,entertaining_relaxing,8,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,FZ0mIU8Ih64,importance,-3,10,2023-05-29,124 -biscuissec,Un67JkVy0xo,FZ0mIU8Ih64,largely_recommended,-2,10,2023-05-29,124 -biscuissec,nU-PdtTcwTk,U_r8O1Henao,importance,-2,10,2023-07-24,132 -biscuissec,nU-PdtTcwTk,U_r8O1Henao,largely_recommended,-4,10,2023-07-24,132 -biscuissec,nU-PdtTcwTk,U_r8O1Henao,entertaining_relaxing,-7,10,2023-07-24,132 -biscuissec,7dkDxmZPWD4,svVFn1XDboo,importance,0,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,svVFn1XDboo,largely_recommended,0,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,svVFn1XDboo,entertaining_relaxing,0,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,JARXHwJoxNk,entertaining_relaxing,-5,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,JARXHwJoxNk,importance,0,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,JARXHwJoxNk,largely_recommended,-1,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,HVTVy-rhP8M,entertaining_relaxing,-1,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,HVTVy-rhP8M,importance,0,10,2023-08-21,136 -biscuissec,7dkDxmZPWD4,HVTVy-rhP8M,largely_recommended,0,10,2023-08-21,136 -biscuissec,kR3JaROyKuA,aIp-aa8F9EI,importance,-7,10,2023-08-28,137 -biscuissec,kR3JaROyKuA,aIp-aa8F9EI,largely_recommended,-4,10,2023-08-28,137 -biscuissec,kR3JaROyKuA,aIp-aa8F9EI,entertaining_relaxing,7,10,2023-08-28,137 -biscuissec,c0Z7KeNCi7g,aIp-aa8F9EI,largely_recommended,-5,10,2023-08-28,137 -biscuissec,c0Z7KeNCi7g,aIp-aa8F9EI,importance,-7,10,2023-08-28,137 -biscuissec,c0Z7KeNCi7g,aIp-aa8F9EI,entertaining_relaxing,-6,10,2023-08-28,137 -biscuissec,WFLy1UrDmXo,ups_V_DwpV8,entertaining_relaxing,8,10,2023-09-11,139 -biscuissec,WFLy1UrDmXo,ups_V_DwpV8,importance,-7,10,2023-09-11,139 -biscuissec,WFLy1UrDmXo,ups_V_DwpV8,largely_recommended,-7,10,2023-09-11,139 -biscuissec,xDjOOxH03hg,PgUN1uy8PYE,largely_recommended,-2,10,2023-09-18,140 -biscuissec,xDjOOxH03hg,PgUN1uy8PYE,importance,-3,10,2023-09-18,140 -biscuissec,xDjOOxH03hg,PgUN1uy8PYE,entertaining_relaxing,0,10,2023-09-18,140 -biscuissec,OJUPi3ytako,PgUN1uy8PYE,entertaining_relaxing,0,10,2023-09-18,140 -biscuissec,OJUPi3ytako,PgUN1uy8PYE,largely_recommended,0,10,2023-09-18,140 -biscuissec,OJUPi3ytako,PgUN1uy8PYE,importance,0,10,2023-09-18,140 -biscuissec,j0YqGziNbUE,U_r8O1Henao,largely_recommended,6,10,2023-09-25,141 -biscuissec,j0YqGziNbUE,U_r8O1Henao,importance,6,10,2023-09-25,141 -biscuissec,j0YqGziNbUE,U_r8O1Henao,entertaining_relaxing,-4,10,2023-09-25,141 -biscuissec,6tOGPPsrysk,U_r8O1Henao,importance,-2,10,2023-10-23,145 -biscuissec,6tOGPPsrysk,U_r8O1Henao,entertaining_relaxing,-2,10,2023-10-23,145 -biscuissec,6tOGPPsrysk,U_r8O1Henao,largely_recommended,-1,10,2023-10-23,145 -biscuissec,KOgt_n8TEqA,7dkDxmZPWD4,largely_recommended,9,10,2023-11-06,147 -biscuissec,KOgt_n8TEqA,7dkDxmZPWD4,importance,9,10,2023-11-06,147 -biscuissec,KOgt_n8TEqA,7dkDxmZPWD4,entertaining_relaxing,9,10,2023-11-06,147 -biscuissec,bVaYBaiVmDM,PgUN1uy8PYE,importance,-4,10,2023-11-13,148 -biscuissec,bVaYBaiVmDM,PgUN1uy8PYE,entertaining_relaxing,-4,10,2023-11-13,148 -biscuissec,bVaYBaiVmDM,PgUN1uy8PYE,largely_recommended,-3,10,2023-11-13,148 -biscuissec,-6k0TSNnK7U,QYg1D1Du1M8,largely_recommended,10,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,J-0zvNL6O3k,largely_recommended,9,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,J-0zvNL6O3k,importance,8,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,eazVPmvLl6Q,importance,9,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,eazVPmvLl6Q,largely_recommended,10,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,eazVPmvLl6Q,entertaining_relaxing,4,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,IqfUaWIC1Ww,importance,9,10,2024-02-05,160 -biscuissec,-6k0TSNnK7U,IqfUaWIC1Ww,largely_recommended,10,10,2024-02-05,160 -biscuissec,p7t1mvM2SVM,fi_U7iDm5c4,importance,1,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,fi_U7iDm5c4,entertaining_relaxing,1,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,fi_U7iDm5c4,largely_recommended,1,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,9a0VCK-RKhU,importance,0,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,9a0VCK-RKhU,entertaining_relaxing,0,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,9a0VCK-RKhU,largely_recommended,0,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,C48PbGgqyDo,entertaining_relaxing,-3,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,C48PbGgqyDo,importance,2,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,C48PbGgqyDo,largely_recommended,0,10,2024-06-17,179 -biscuissec,p7t1mvM2SVM,C9C8f2b1268,largely_recommended,3,10,2024-06-17,179 -biscuissec,4njJV3ow2z4,u3iJKE3PdEM,entertaining_relaxing,-3,10,2024-12-09,204 -biscuissec,4njJV3ow2z4,u3iJKE3PdEM,importance,-1,10,2024-12-09,204 -biscuissec,4njJV3ow2z4,u3iJKE3PdEM,largely_recommended,-2,10,2024-12-09,204 -biscuissec,c6ALoH2S6sA,u3iJKE3PdEM,largely_recommended,-1,10,2024-12-09,204 -biscuissec,c6ALoH2S6sA,u3iJKE3PdEM,importance,0,10,2024-12-09,204 -biscuissec,c6ALoH2S6sA,u3iJKE3PdEM,entertaining_relaxing,0,10,2024-12-09,204 -Foebus,wfb1oyiisqs,DlIUhG3O-Yo,entertaining_relaxing,3,10,2022-02-14,57 -Foebus,wfb1oyiisqs,DlIUhG3O-Yo,largely_recommended,-3,10,2022-02-14,57 -Foebus,wfb1oyiisqs,DlIUhG3O-Yo,importance,-5,10,2022-02-14,57 -Foebus,wfb1oyiisqs,0aZ2CtRCF-A,largely_recommended,2,10,2022-02-28,59 -Foebus,wfb1oyiisqs,0aZ2CtRCF-A,importance,-4,10,2022-02-28,59 -Foebus,wfb1oyiisqs,0aZ2CtRCF-A,entertaining_relaxing,-2,10,2022-02-28,59 -Foebus,wfb1oyiisqs,LkoGBOs5ecM,largely_recommended,-3,10,2022-02-28,59 -Foebus,wfb1oyiisqs,LkoGBOs5ecM,importance,-6,10,2022-02-28,59 -Foebus,wfb1oyiisqs,LkoGBOs5ecM,entertaining_relaxing,4,10,2022-02-28,59 -Foebus,wfb1oyiisqs,url1TFdHlSI,importance,1,10,2022-03-14,61 -Foebus,wfb1oyiisqs,url1TFdHlSI,largely_recommended,2,10,2022-03-14,61 -Foebus,wfb1oyiisqs,url1TFdHlSI,entertaining_relaxing,-4,10,2022-03-14,61 -Foebus,Eot3bdeElpg,wfb1oyiisqs,entertaining_relaxing,3,10,2022-03-07,60 -Foebus,Eot3bdeElpg,wfb1oyiisqs,importance,5,10,2022-03-07,60 -Foebus,Eot3bdeElpg,wfb1oyiisqs,largely_recommended,4,10,2022-03-07,60 -Foebus,4Y1Cfa5VVNI,wfb1oyiisqs,importance,5,10,2022-04-04,64 -Foebus,4Y1Cfa5VVNI,wfb1oyiisqs,entertaining_relaxing,3,10,2022-04-04,64 -Foebus,4Y1Cfa5VVNI,wfb1oyiisqs,largely_recommended,5,10,2022-04-04,64 -Foebus,FA7G1bagOFY,q_AL1ROAJ6c,largely_recommended,5,10,2022-04-25,67 -Foebus,FA7G1bagOFY,uZEumZFFfX0,largely_recommended,5,10,2022-04-25,67 -Foebus,xWex5aTnneU,EfRCYDsxNwo,largely_recommended,-6,10,2023-10-02,142 -Foebus,2ER1KAkn_JQ,EfRCYDsxNwo,largely_recommended,3,10,2023-10-02,142 -Foebus,sAhMJYLDAKQ,EfRCYDsxNwo,largely_recommended,4,10,2023-10-02,142 -Foebus,8d0TcPOaABE,wfb1oyiisqs,largely_recommended,-4,10,2024-02-05,160 -Foebus,ZP7T6WAK3Ow,eJTIo_MhG3M,largely_recommended,-10,10,2024-10-14,196 -Foebus,ZP7T6WAK3Ow,iW0LiIMYqrU,largely_recommended,3,10,2024-12-02,203 -Foebus,ZP7T6WAK3Ow,CwPB_NiP_Dc,largely_recommended,-9,10,2024-12-02,203 -Foebus,ZP7T6WAK3Ow,KcHJv4TlwMQ,largely_recommended,-7,10,2024-12-02,203 -Foebus,ZP7T6WAK3Ow,GxNPxaPwluY,largely_recommended,2,10,2024-12-02,203 -Fungus-Bob,OhCzX0iLnOc,SPAmbUZ9UKk,entertaining_relaxing,3,10,2022-04-11,65 -Fungus-Bob,OhCzX0iLnOc,SPAmbUZ9UKk,largely_recommended,7,10,2022-04-11,65 -Fungus-Bob,OhCzX0iLnOc,SPAmbUZ9UKk,importance,5,10,2022-04-11,65 -Fungus-Bob,MvFbxQ-d8hE,cGoWEBEEUQw,importance,-3,10,2022-12-19,101 -Fungus-Bob,MvFbxQ-d8hE,cGoWEBEEUQw,largely_recommended,-4,10,2022-12-19,101 -Fungus-Bob,MvFbxQ-d8hE,cGoWEBEEUQw,entertaining_relaxing,0,10,2022-12-19,101 -Fungus-Bob,se7tPtdC5bA,cGoWEBEEUQw,importance,-1,10,2022-12-26,102 -Fungus-Bob,se7tPtdC5bA,cGoWEBEEUQw,entertaining_relaxing,-2,10,2022-12-26,102 -Fungus-Bob,se7tPtdC5bA,cGoWEBEEUQw,largely_recommended,-3,10,2022-12-26,102 -Fungus-Bob,F7pYHN9iC9I,cGoWEBEEUQw,importance,-2,10,2022-12-26,102 -Fungus-Bob,F7pYHN9iC9I,cGoWEBEEUQw,largely_recommended,-3,10,2022-12-26,102 -Fungus-Bob,F7pYHN9iC9I,cGoWEBEEUQw,entertaining_relaxing,-4,10,2022-12-26,102 -Fungus-Bob,o1zNIm8GVPY,cGoWEBEEUQw,largely_recommended,-1,10,2022-12-26,102 -Fungus-Bob,o1zNIm8GVPY,cGoWEBEEUQw,importance,-2,10,2022-12-26,102 -Fungus-Bob,o1zNIm8GVPY,cGoWEBEEUQw,entertaining_relaxing,-3,10,2022-12-26,102 -Fungus-Bob,fksKuXhvWX4,KtaFpu2aJME,largely_recommended,-6,10,2023-02-13,109 -Fungus-Bob,fksKuXhvWX4,KtaFpu2aJME,entertaining_relaxing,0,10,2023-02-13,109 -Fungus-Bob,fksKuXhvWX4,KtaFpu2aJME,importance,-4,10,2023-02-13,109 -Fungus-Bob,fksKuXhvWX4,TLBWxkx59yc,largely_recommended,1,10,2023-02-13,109 -Fungus-Bob,fksKuXhvWX4,TLBWxkx59yc,entertaining_relaxing,5,10,2023-02-13,109 -Fungus-Bob,fksKuXhvWX4,TLBWxkx59yc,importance,-4,10,2023-02-13,109 -Fungus-Bob,fTfapvfyxEQ,fksKuXhvWX4,importance,7,10,2023-02-13,109 -Fungus-Bob,fTfapvfyxEQ,fksKuXhvWX4,entertaining_relaxing,2,10,2023-02-13,109 -Fungus-Bob,fTfapvfyxEQ,fksKuXhvWX4,largely_recommended,9,10,2023-02-13,109 -Guigui220D,oAMM3l156Oo,d8ntTETk2F0,entertaining_relaxing,2,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,d8ntTETk2F0,importance,0,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,d8ntTETk2F0,largely_recommended,1,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,odjlvDyy6h8,largely_recommended,-6,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,odjlvDyy6h8,importance,-4,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,nv1xgQ6B5hs,largely_recommended,-5,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,nv1xgQ6B5hs,importance,-6,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,nv1xgQ6B5hs,entertaining_relaxing,2,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,Aj7PKDTrbjQ,largely_recommended,0,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,Aj7PKDTrbjQ,importance,-3,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,Aj7PKDTrbjQ,entertaining_relaxing,4,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,R2fjRbc9Sa0,largely_recommended,-5,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,R2fjRbc9Sa0,importance,-6,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,R2fjRbc9Sa0,entertaining_relaxing,2,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,75bbNdlX2pA,largely_recommended,-3,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,75bbNdlX2pA,importance,0,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,75bbNdlX2pA,entertaining_relaxing,0,10,2023-01-16,105 -Guigui220D,oAMM3l156Oo,Y71mvOIpkWE,entertaining_relaxing,-6,10,2023-01-23,106 -Guigui220D,oAMM3l156Oo,Y71mvOIpkWE,largely_recommended,4,10,2023-01-23,106 -Guigui220D,oAMM3l156Oo,Y71mvOIpkWE,importance,5,10,2023-01-23,106 -Guigui220D,75bbNdlX2pA,I9hJ_Rux9y0,importance,-4,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,I9hJ_Rux9y0,largely_recommended,-3,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,I9hJ_Rux9y0,entertaining_relaxing,5,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,d8ntTETk2F0,entertaining_relaxing,2,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,d8ntTETk2F0,importance,3,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,d8ntTETk2F0,largely_recommended,2,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,_DPKnv4W25Q,largely_recommended,4,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,_DPKnv4W25Q,importance,5,10,2023-01-16,105 -Guigui220D,75bbNdlX2pA,_DPKnv4W25Q,entertaining_relaxing,5,10,2023-01-16,105 -Guigui220D,Dbi_vhEPO8Y,75bbNdlX2pA,importance,0,10,2023-01-16,105 -Guigui220D,Dbi_vhEPO8Y,75bbNdlX2pA,largely_recommended,-3,10,2023-01-16,105 -Guigui220D,7jqkvs8vGnk,75bbNdlX2pA,entertaining_relaxing,-2,10,2023-01-16,105 -Guigui220D,7jqkvs8vGnk,75bbNdlX2pA,importance,0,10,2023-01-16,105 -Guigui220D,7jqkvs8vGnk,75bbNdlX2pA,largely_recommended,2,10,2023-01-16,105 -Guigui220D,6JjRS4rz7A8,75bbNdlX2pA,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,6JjRS4rz7A8,75bbNdlX2pA,importance,3,10,2023-01-23,106 -Guigui220D,6JjRS4rz7A8,75bbNdlX2pA,largely_recommended,0,10,2023-01-23,106 -Guigui220D,fQtGTIpVuy0,oAMM3l156Oo,importance,3,10,2023-01-23,106 -Guigui220D,fQtGTIpVuy0,oAMM3l156Oo,entertaining_relaxing,-2,10,2023-01-23,106 -Guigui220D,fQtGTIpVuy0,oAMM3l156Oo,largely_recommended,3,10,2023-01-23,106 -Guigui220D,Xi-HWyh0Ybk,oAMM3l156Oo,importance,4,10,2023-01-23,106 -Guigui220D,Xi-HWyh0Ybk,oAMM3l156Oo,entertaining_relaxing,-3,10,2023-01-23,106 -Guigui220D,Xi-HWyh0Ybk,oAMM3l156Oo,largely_recommended,2,10,2023-01-23,106 -Guigui220D,JXeJANDKwDc,uljTEmmCh_E,importance,0,10,2023-01-23,106 -Guigui220D,JXeJANDKwDc,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,JXeJANDKwDc,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -Guigui220D,d35JQvaEen0,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -Guigui220D,d35JQvaEen0,uljTEmmCh_E,importance,0,10,2023-01-23,106 -Guigui220D,d35JQvaEen0,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,9BBqFZwBsgs,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -Guigui220D,9BBqFZwBsgs,uljTEmmCh_E,importance,0,10,2023-01-23,106 -Guigui220D,9BBqFZwBsgs,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,bAn5zcG8-HA,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -Guigui220D,bAn5zcG8-HA,uljTEmmCh_E,importance,0,10,2023-01-23,106 -Guigui220D,bAn5zcG8-HA,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,7WGaMAb-ivs,largely_recommended,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,7WGaMAb-ivs,importance,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,7WGaMAb-ivs,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,K9UE2WD6nu8,largely_recommended,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,K9UE2WD6nu8,entertaining_relaxing,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,K9UE2WD6nu8,importance,0,10,2023-01-23,106 -Guigui220D,uljTEmmCh_E,uYYRAPBbr_w,largely_recommended,0,10,2023-02-27,111 -Guigui220D,uljTEmmCh_E,uYYRAPBbr_w,entertaining_relaxing,0,10,2023-02-27,111 -Guigui220D,uljTEmmCh_E,uYYRAPBbr_w,importance,0,10,2023-02-27,111 -Guigui220D,BCPNzCRKFCg,uljTEmmCh_E,importance,0,10,2023-01-30,107 -Guigui220D,BCPNzCRKFCg,uljTEmmCh_E,largely_recommended,4,10,2023-01-30,107 -Guigui220D,BCPNzCRKFCg,uljTEmmCh_E,entertaining_relaxing,4,10,2023-01-30,107 -Guigui220D,nh1cz49hp6Y,dBjzG1k7jso,importance,7,10,2023-03-06,112 -Guigui220D,nh1cz49hp6Y,dBjzG1k7jso,entertaining_relaxing,0,10,2023-03-06,112 -Guigui220D,nh1cz49hp6Y,dBjzG1k7jso,largely_recommended,5,10,2023-03-06,112 -Guigui220D,GSvTFIho5D8,nh1cz49hp6Y,largely_recommended,-4,10,2023-03-06,112 -Guigui220D,GSvTFIho5D8,nh1cz49hp6Y,importance,-5,10,2023-03-06,112 -Guigui220D,GSvTFIho5D8,nh1cz49hp6Y,entertaining_relaxing,4,10,2023-03-06,112 -Guigui220D,r1QmanljNTw,nh1cz49hp6Y,largely_recommended,-6,10,2023-03-06,112 -Guigui220D,r1QmanljNTw,nh1cz49hp6Y,importance,-8,10,2023-03-06,112 -Guigui220D,r1QmanljNTw,nh1cz49hp6Y,entertaining_relaxing,6,10,2023-03-06,112 -Guigui220D,9rIy0xY99a0,nh1cz49hp6Y,largely_recommended,1,10,2023-03-13,113 -Guigui220D,9rIy0xY99a0,nh1cz49hp6Y,importance,2,10,2023-03-13,113 -Guigui220D,9rIy0xY99a0,nh1cz49hp6Y,entertaining_relaxing,-4,10,2023-03-13,113 -Guigui220D,IzAB_42Pqew,nh1cz49hp6Y,largely_recommended,-2,10,2023-03-13,113 -Guigui220D,IzAB_42Pqew,nh1cz49hp6Y,importance,-6,10,2023-03-13,113 -Guigui220D,IzAB_42Pqew,nh1cz49hp6Y,entertaining_relaxing,7,10,2023-03-13,113 -Guigui220D,Rz_U7WuS2UM,nh1cz49hp6Y,largely_recommended,-4,10,2023-03-27,115 -Guigui220D,Rz_U7WuS2UM,nh1cz49hp6Y,importance,-4,10,2023-03-27,115 -Guigui220D,Rz_U7WuS2UM,nh1cz49hp6Y,entertaining_relaxing,3,10,2023-03-27,115 -joleenj,xeMbGBw7j8g,qwFSHelaMV4,largely_recommended,4,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,qwFSHelaMV4,entertaining_relaxing,0,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,qwFSHelaMV4,importance,3,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,gW3oWM0Uefk,largely_recommended,0,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,gW3oWM0Uefk,importance,0,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,gW3oWM0Uefk,entertaining_relaxing,7,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,q_AL1ROAJ6c,largely_recommended,-4,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,q_AL1ROAJ6c,importance,-4,10,2022-02-28,59 -joleenj,xeMbGBw7j8g,q_AL1ROAJ6c,entertaining_relaxing,5,10,2022-02-28,59 -joleenj,kok3UIjTMwY,xeMbGBw7j8g,entertaining_relaxing,1,10,2022-02-28,59 -joleenj,kok3UIjTMwY,xeMbGBw7j8g,importance,-2,10,2022-02-28,59 -joleenj,kok3UIjTMwY,xeMbGBw7j8g,largely_recommended,-2,10,2022-02-28,59 -joleenj,-aTLKQpEel4,xeMbGBw7j8g,largely_recommended,-3,10,2022-02-28,59 -joleenj,-aTLKQpEel4,xeMbGBw7j8g,importance,0,10,2022-02-28,59 -joleenj,3SMBV0gHVKQ,xeMbGBw7j8g,importance,-3,10,2022-02-28,59 -joleenj,3SMBV0gHVKQ,xeMbGBw7j8g,largely_recommended,-5,10,2022-02-28,59 -joleenj,KPUlgSRn6e0,U51myW8o1YA,largely_recommended,-8,10,2023-01-02,103 -joleenj,KPUlgSRn6e0,U51myW8o1YA,importance,-8,10,2023-01-02,103 -joleenj,KPUlgSRn6e0,U51myW8o1YA,entertaining_relaxing,0,10,2023-01-02,103 -joleenj,V6ChTqII-Yk,q-ApAdEOm5s,importance,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,q-ApAdEOm5s,largely_recommended,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,q-ApAdEOm5s,entertaining_relaxing,0,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,DP7Sa4c-j7o,entertaining_relaxing,4,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,DP7Sa4c-j7o,importance,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,DP7Sa4c-j7o,largely_recommended,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,sauR0D-pnwg,entertaining_relaxing,-5,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,sauR0D-pnwg,importance,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,sauR0D-pnwg,largely_recommended,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,OY1BUOd6mm0,largely_recommended,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,OY1BUOd6mm0,importance,-10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,OY1BUOd6mm0,entertaining_relaxing,10,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,1t6hoJNXugM,entertaining_relaxing,0,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,1t6hoJNXugM,largely_recommended,0,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,1t6hoJNXugM,importance,0,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,mXLqrMljdfU,entertaining_relaxing,0,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,mXLqrMljdfU,importance,-3,10,2023-01-09,104 -joleenj,V6ChTqII-Yk,mXLqrMljdfU,largely_recommended,-4,10,2023-01-09,104 -joleenj,SbjGMdRQhxw,i5AwY7QBtrA,largely_recommended,-10,10,2023-06-05,125 -joleenj,SbjGMdRQhxw,i5AwY7QBtrA,entertaining_relaxing,4,10,2023-06-05,125 -joleenj,SbjGMdRQhxw,i5AwY7QBtrA,importance,-8,10,2023-06-05,125 -lafabriquesociale,C_gMPaP8x5I,6lVBp2XjWsg,entertaining_relaxing,-5,10,2023-09-11,139 -lafabriquesociale,C_gMPaP8x5I,6lVBp2XjWsg,importance,-5,10,2023-09-11,139 -lafabriquesociale,C_gMPaP8x5I,6lVBp2XjWsg,largely_recommended,-6,10,2023-09-11,139 -le_science4all,v_TGhhUfwgI,2Z9p_I3hhUc,importance,-10,10,2021-01-11,0 -le_science4all,2Z9p_I3hhUc,v9EKV2nSU8w,importance,6,10,2021-01-11,0 -le_science4all,2Z9p_I3hhUc,n6QwnzbRUyA,importance,-6,10,2021-01-11,0 -le_science4all,2Z9p_I3hhUc,ua5aOFi-DKs,importance,6,10,2021-01-11,0 -le_science4all,2Z9p_I3hhUc,850Zr6dzxYU,importance,5,10,2021-01-11,0 -le_science4all,2Z9p_I3hhUc,eW8UfbDSmjQ,largely_recommended,-1,10,2022-09-05,86 -le_science4all,2Z9p_I3hhUc,dGJzpQwA090,largely_recommended,8,10,2022-11-28,98 -le_science4all,M_gShd4tKQU,D9N7QaIOkG8,importance,8,10,2022-01-17,53 -le_science4all,M_gShd4tKQU,D9N7QaIOkG8,entertaining_relaxing,-2,10,2022-01-17,53 -le_science4all,M_gShd4tKQU,D9N7QaIOkG8,largely_recommended,3,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,TDD8FgidmzM,entertaining_relaxing,3,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,TDD8FgidmzM,importance,8,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,TDD8FgidmzM,largely_recommended,7,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,S-W0NX97DB0,largely_recommended,6,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,S-W0NX97DB0,entertaining_relaxing,7,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,S-W0NX97DB0,importance,5,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,qZRYGxF6D3w,importance,0,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,qZRYGxF6D3w,entertaining_relaxing,6,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,qZRYGxF6D3w,largely_recommended,1,10,2022-01-17,53 -le_science4all,SBwupYwDgHg,4RflQ5NghjE,largely_recommended,8,10,2022-08-15,83 -le_science4all,G6N5DZLDja8,tti8b__ld1U,largely_recommended,7,10,2022-01-17,53 -le_science4all,G6N5DZLDja8,tti8b__ld1U,entertaining_relaxing,0,10,2022-01-17,53 -le_science4all,G6N5DZLDja8,tti8b__ld1U,importance,8,10,2022-01-17,53 -le_science4all,OkmNXy7er84,tti8b__ld1U,largely_recommended,7,10,2022-01-17,53 -le_science4all,OkmNXy7er84,tti8b__ld1U,importance,9,10,2022-01-17,53 -le_science4all,OkmNXy7er84,tti8b__ld1U,entertaining_relaxing,-2,10,2022-01-17,53 -le_science4all,kxkrdLI6e6M,tti8b__ld1U,entertaining_relaxing,-3,10,2022-01-17,53 -le_science4all,kxkrdLI6e6M,tti8b__ld1U,importance,7,10,2022-01-17,53 -le_science4all,kxkrdLI6e6M,tti8b__ld1U,largely_recommended,6,10,2022-01-17,53 -le_science4all,q_AL1ROAJ6c,D9N7QaIOkG8,largely_recommended,10,10,2022-01-17,53 -le_science4all,q_AL1ROAJ6c,D9N7QaIOkG8,entertaining_relaxing,-3,10,2022-01-17,53 -le_science4all,q_AL1ROAJ6c,D9N7QaIOkG8,importance,5,10,2022-01-17,53 -le_science4all,jgZ3CIlwRic,D9N7QaIOkG8,largely_recommended,5,10,2022-01-17,53 -le_science4all,jgZ3CIlwRic,D9N7QaIOkG8,importance,8,10,2022-01-17,53 -le_science4all,jgZ3CIlwRic,D9N7QaIOkG8,entertaining_relaxing,1,10,2022-01-17,53 -le_science4all,QR3BCuJwjA4,p5SPFOABCGU,importance,8,10,2022-01-31,55 -le_science4all,QR3BCuJwjA4,p5SPFOABCGU,largely_recommended,7,10,2022-01-31,55 -le_science4all,QR3BCuJwjA4,p5SPFOABCGU,entertaining_relaxing,5,10,2022-01-31,55 -le_science4all,1zskDU0uDcI,p5SPFOABCGU,largely_recommended,-4,10,2022-01-31,55 -le_science4all,1zskDU0uDcI,p5SPFOABCGU,importance,-4,10,2022-01-31,55 -le_science4all,1zskDU0uDcI,p5SPFOABCGU,entertaining_relaxing,3,10,2022-01-31,55 -le_science4all,H7o1A6oX1cY,p5SPFOABCGU,largely_recommended,6,10,2022-01-31,55 -le_science4all,H7o1A6oX1cY,p5SPFOABCGU,importance,7,10,2022-01-31,55 -le_science4all,H7o1A6oX1cY,p5SPFOABCGU,entertaining_relaxing,6,10,2022-01-31,55 -le_science4all,-gL6snFrUe0,tti8b__ld1U,largely_recommended,-3,10,2022-02-21,58 -le_science4all,-gL6snFrUe0,tti8b__ld1U,importance,-5,10,2022-02-21,58 -le_science4all,-gL6snFrUe0,tti8b__ld1U,entertaining_relaxing,0,10,2022-02-21,58 -le_science4all,tti8b__ld1U,XPxIkXDGgqo,largely_recommended,3,10,2022-02-21,58 -le_science4all,wmDsQS2-I1E,tti8b__ld1U,largely_recommended,4,10,2022-02-21,58 -le_science4all,wmDsQS2-I1E,tti8b__ld1U,importance,6,10,2022-02-21,58 -le_science4all,wmDsQS2-I1E,tti8b__ld1U,entertaining_relaxing,0,10,2022-02-21,58 -le_science4all,VM6HZqQKhok,LXVa9HCHa_M,importance,-10,10,2022-03-21,62 -le_science4all,VM6HZqQKhok,LXVa9HCHa_M,largely_recommended,-9,10,2022-03-21,62 -le_science4all,VM6HZqQKhok,LXVa9HCHa_M,entertaining_relaxing,-10,10,2022-03-21,62 -le_science4all,qF1DTK4U1AM,LXVa9HCHa_M,entertaining_relaxing,-10,10,2022-03-21,62 -le_science4all,qF1DTK4U1AM,LXVa9HCHa_M,importance,-5,10,2022-03-21,62 -le_science4all,qF1DTK4U1AM,LXVa9HCHa_M,largely_recommended,-6,10,2022-03-21,62 -le_science4all,lG4VkPoG3ko,LXVa9HCHa_M,entertaining_relaxing,-2,10,2022-03-21,62 -le_science4all,lG4VkPoG3ko,LXVa9HCHa_M,importance,-9,10,2022-03-21,62 -le_science4all,lG4VkPoG3ko,LXVa9HCHa_M,largely_recommended,-8,10,2022-03-21,62 -le_science4all,4L77Qg53Rjw,IV3dnLzthDA,importance,6,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,IV3dnLzthDA,entertaining_relaxing,8,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,IV3dnLzthDA,largely_recommended,8,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,KyeJTbFCSv0,entertaining_relaxing,-5,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,KyeJTbFCSv0,largely_recommended,7,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,KyeJTbFCSv0,importance,5,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,tEQc3jLKtY8,entertaining_relaxing,0,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,tEQc3jLKtY8,importance,9,10,2022-04-25,67 -le_science4all,4L77Qg53Rjw,tEQc3jLKtY8,largely_recommended,6,10,2022-04-25,67 -le_science4all,qPcm7Q6e0ZM,tti8b__ld1U,largely_recommended,10,10,2022-06-20,75 -le_science4all,XRk2VeL0icU,IMsaI4RfP2E,importance,-6,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,IMsaI4RfP2E,largely_recommended,-5,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,IMsaI4RfP2E,entertaining_relaxing,-5,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,url1TFdHlSI,importance,4,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,url1TFdHlSI,largely_recommended,5,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,url1TFdHlSI,entertaining_relaxing,1,10,2022-07-11,78 -le_science4all,XRk2VeL0icU,8b3lhDyVqgk,largely_recommended,3,10,2022-07-11,78 -le_science4all,MVhankVI_Vo,wtxy-0tis_g,entertaining_relaxing,4,10,2022-07-11,78 -le_science4all,MVhankVI_Vo,wtxy-0tis_g,importance,-5,10,2022-07-11,78 -le_science4all,MVhankVI_Vo,wtxy-0tis_g,largely_recommended,0,10,2022-07-11,78 -le_science4all,xPm7zOFSJgk,wtxy-0tis_g,largely_recommended,-6,10,2022-07-11,78 -le_science4all,xPm7zOFSJgk,wtxy-0tis_g,importance,-6,10,2022-07-11,78 -le_science4all,xPm7zOFSJgk,wtxy-0tis_g,entertaining_relaxing,-9,10,2022-07-11,78 -le_science4all,wtxy-0tis_g,2ty2J0s2W0c,importance,8,10,2022-07-11,78 -le_science4all,wtxy-0tis_g,2ty2J0s2W0c,largely_recommended,6,10,2022-07-11,78 -le_science4all,wtxy-0tis_g,2ty2J0s2W0c,entertaining_relaxing,-4,10,2022-07-11,78 -le_science4all,wtxy-0tis_g,p-VuRpkrNto,largely_recommended,2,10,2022-07-11,78 -le_science4all,4RTxJ_I9LtU,XRk2VeL0icU,largely_recommended,4,10,2022-07-11,78 -le_science4all,D9N7QaIOkG8,LXVa9HCHa_M,largely_recommended,-3,10,2022-07-25,80 -le_science4all,D9N7QaIOkG8,wtJwVZGuiOY,largely_recommended,0,10,2023-06-12,126 -le_science4all,zrFzSwHxiBQ,k3bkNewAR5U,entertaining_relaxing,-5,10,2022-08-15,83 -le_science4all,zrFzSwHxiBQ,k3bkNewAR5U,importance,8,10,2022-08-15,83 -le_science4all,zrFzSwHxiBQ,k3bkNewAR5U,largely_recommended,2,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,x2hw_ghPcQs,importance,4,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,x2hw_ghPcQs,entertaining_relaxing,9,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,x2hw_ghPcQs,largely_recommended,4,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,xjeaL-YseZk,largely_recommended,-9,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,xjeaL-YseZk,importance,-10,10,2022-08-15,83 -le_science4all,k3bkNewAR5U,xjeaL-YseZk,entertaining_relaxing,0,10,2022-08-15,83 -le_science4all,QeuIBwh7xNQ,k3bkNewAR5U,largely_recommended,-4,10,2022-08-15,83 -le_science4all,ju6hC1YF5TM,LC9J6p4SBY8,largely_recommended,0,10,2022-09-12,87 -le_science4all,ju6hC1YF5TM,LC9J6p4SBY8,importance,6,10,2022-09-12,87 -le_science4all,ju6hC1YF5TM,LC9J6p4SBY8,entertaining_relaxing,-6,10,2022-09-12,87 -le_science4all,ienoSbONyhw,SBwupYwDgHg,largely_recommended,-5,10,2022-09-26,89 -le_science4all,ienoSbONyhw,SBwupYwDgHg,entertaining_relaxing,0,10,2022-09-26,89 -le_science4all,ienoSbONyhw,SBwupYwDgHg,importance,-8,10,2022-09-26,89 -le_science4all,qTrfBMH2Nfc,XRk2VeL0icU,largely_recommended,9,10,2022-09-26,89 -le_science4all,xeMbGBw7j8g,l1WQHiNux6g,largely_recommended,2,10,2022-10-03,90 -le_science4all,xeMbGBw7j8g,9Tbb5gcpk4w,largely_recommended,-6,10,2024-03-11,165 -le_science4all,v3n8txX3144,4L77Qg53Rjw,largely_recommended,-6,10,2022-10-10,91 -le_science4all,m8g_b8PuOdI,LXVa9HCHa_M,largely_recommended,-4,10,2022-11-28,98 -le_science4all,C_gMPaP8x5I,rNGVsoVvXDQ,largely_recommended,-2,10,2023-02-27,111 -le_science4all,C_gMPaP8x5I,3-KzTAdmMOw,entertaining_relaxing,-2,10,2023-02-27,111 -le_science4all,C_gMPaP8x5I,3-KzTAdmMOw,importance,-1,10,2023-02-27,111 -le_science4all,C_gMPaP8x5I,3-KzTAdmMOw,largely_recommended,-5,10,2023-02-27,111 -le_science4all,C_gMPaP8x5I,V2_ttvNDAno,largely_recommended,-4,10,2023-02-27,111 -le_science4all,C_gMPaP8x5I,KOZnI0v87RA,largely_recommended,-7,10,2023-02-27,111 -le_science4all,NDlQrK_QAzY,FU_YFpfDqqA,importance,-2,10,2023-05-22,123 -le_science4all,NDlQrK_QAzY,FU_YFpfDqqA,largely_recommended,10,10,2023-05-22,123 -le_science4all,NDlQrK_QAzY,FU_YFpfDqqA,entertaining_relaxing,8,10,2023-05-22,123 -le_science4all,ZnnFeSCZTxQ,NDlQrK_QAzY,largely_recommended,-10,10,2023-05-22,123 -le_science4all,a4tbf-ftbds,NDlQrK_QAzY,largely_recommended,-10,10,2023-05-22,123 -le_science4all,RW1zX00L1jY,NDlQrK_QAzY,largely_recommended,-10,10,2023-05-22,123 -le_science4all,cK5bRzmQTLE,D9N7QaIOkG8,largely_recommended,9,10,2023-05-29,124 -le_science4all,M0WWJ7bzOSk,D9N7QaIOkG8,largely_recommended,9,10,2023-05-29,124 -le_science4all,hxsplC0xPlY,xeMbGBw7j8g,largely_recommended,4,10,2023-11-13,148 -le_science4all,8k3V8OVQR0s,2Z9p_I3hhUc,largely_recommended,0,10,2023-11-13,148 -le_science4all,PrjdUNS-p4s,4L77Qg53Rjw,largely_recommended,9,10,2024-02-19,162 -le_science4all,6REilAGNKGs,nyGrd6w65Ao,largely_recommended,-1,10,2024-04-15,170 -le_science4all,6REilAGNKGs,Hr25C-_wiPg,largely_recommended,-3,10,2024-04-15,170 -le_science4all,6REilAGNKGs,-Od0UgFojYY,largely_recommended,-4,10,2024-04-15,170 -le_science4all,A88i4kpylik,D9N7QaIOkG8,largely_recommended,-5,10,2024-04-29,172 -le_science4all,ZkMP6YD52L8,dmiwYCbGifA,largely_recommended,4,10,2024-07-15,183 -le_science4all,ZkMP6YD52L8,YOMp8Wshiqs,largely_recommended,-2,10,2024-07-15,183 -le_science4all,ZkMP6YD52L8,vnIIVeCBJuw,largely_recommended,-2,10,2024-07-15,183 -le_science4all,fQvycccJVqQ,D9N7QaIOkG8,largely_recommended,0,10,2024-07-29,185 -le_science4all,MmOYmPM7OFE,Uod1RAyJaxg,largely_recommended,-3,10,2024-08-26,189 -le_science4all,MmOYmPM7OFE,RBfrPmM0_kM,largely_recommended,0,10,2024-08-26,189 -le_science4all,MmOYmPM7OFE,FU_YFpfDqqA,largely_recommended,-1,10,2024-08-26,189 -le_science4all,e3fz3dqhN44,LXVa9HCHa_M,largely_recommended,8,10,2024-09-30,194 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-lpfaucon,IS7vz55_IS0,y1ljywmHXsQ,largely_recommended,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,y1ljywmHXsQ,entertaining_relaxing,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,Xz7AtVkjdmk,importance,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,Xz7AtVkjdmk,largely_recommended,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,Xz7AtVkjdmk,entertaining_relaxing,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,X_rp5slf3c4,largely_recommended,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,X_rp5slf3c4,importance,5,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,X_rp5slf3c4,entertaining_relaxing,5,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,VHuZTjp7XbU,largely_recommended,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,VHuZTjp7XbU,entertaining_relaxing,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,VHuZTjp7XbU,importance,10,10,2021-04-19,14 -lpfaucon,IS7vz55_IS0,HNJPasJUGqs,largely_recommended,6,10,2023-07-03,129 -lpfaucon,IS7vz55_IS0,JMpuxLIgjPs,entertaining_relaxing,10,10,2023-07-03,129 -lpfaucon,IS7vz55_IS0,JMpuxLIgjPs,importance,10,10,2023-07-03,129 -lpfaucon,IS7vz55_IS0,JMpuxLIgjPs,largely_recommended,10,10,2023-07-03,129 -lpfaucon,ap6VS5anhCc,IS7vz55_IS0,entertaining_relaxing,-10,10,2021-04-19,14 -lpfaucon,ap6VS5anhCc,IS7vz55_IS0,largely_recommended,-10,10,2021-04-19,14 -lpfaucon,ap6VS5anhCc,IS7vz55_IS0,importance,-10,10,2021-04-19,14 -lpfaucon,Hug0rfFC_L8,IS7vz55_IS0,largely_recommended,-10,10,2021-04-19,14 -lpfaucon,Hug0rfFC_L8,IS7vz55_IS0,importance,-10,10,2021-04-19,14 -lpfaucon,Hug0rfFC_L8,IS7vz55_IS0,entertaining_relaxing,-10,10,2021-04-19,14 -lpfaucon,xeMbGBw7j8g,YOZbvw00qgI,importance,-2,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,YOZbvw00qgI,entertaining_relaxing,3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,YOZbvw00qgI,largely_recommended,2,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,CsfMCNEN9dw,entertaining_relaxing,3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,CsfMCNEN9dw,largely_recommended,-9,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,CsfMCNEN9dw,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,m62QcCAkm88,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,m62QcCAkm88,entertaining_relaxing,3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,m62QcCAkm88,largely_recommended,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,YEbQgKIXWVc,entertaining_relaxing,7,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,YEbQgKIXWVc,largely_recommended,-8,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,YEbQgKIXWVc,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,d1Des_7CBxY,importance,-3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,d1Des_7CBxY,entertaining_relaxing,4,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,d1Des_7CBxY,largely_recommended,4,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,EzkWqpsPqho,entertaining_relaxing,-5,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,EzkWqpsPqho,largely_recommended,-5,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,EzkWqpsPqho,importance,-5,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,b0kzTgz-y4Y,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,b0kzTgz-y4Y,largely_recommended,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,b0kzTgz-y4Y,entertaining_relaxing,-2,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,zs7Ye1BVkoo,largely_recommended,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,zs7Ye1BVkoo,entertaining_relaxing,10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,zs7Ye1BVkoo,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,dLRLYPiaAoA,importance,-8,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,dLRLYPiaAoA,largely_recommended,0,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,dLRLYPiaAoA,entertaining_relaxing,10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,7HHA-fvgoq8,entertaining_relaxing,-3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,7HHA-fvgoq8,largely_recommended,-3,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,7HHA-fvgoq8,importance,2,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,AmgkSdhK4K8,entertaining_relaxing,4,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,AmgkSdhK4K8,largely_recommended,-6,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,AmgkSdhK4K8,importance,-10,10,2021-05-17,18 -lpfaucon,xeMbGBw7j8g,hy_9RZRAXbA,largely_recommended,5,10,2021-10-04,38 -lpfaucon,xeMbGBw7j8g,hy_9RZRAXbA,entertaining_relaxing,-5,10,2021-10-04,38 -lpfaucon,xeMbGBw7j8g,hy_9RZRAXbA,importance,5,10,2021-10-04,38 -lpfaucon,xeMbGBw7j8g,Nvg2-mJr4Hw,entertaining_relaxing,2,10,2022-04-25,67 -lpfaucon,xeMbGBw7j8g,Nvg2-mJr4Hw,importance,-7,10,2022-04-25,67 -lpfaucon,xeMbGBw7j8g,Nvg2-mJr4Hw,largely_recommended,-9,10,2022-04-25,67 -lpfaucon,xeMbGBw7j8g,Ga-p11MVYzs,entertaining_relaxing,-3,10,2022-06-06,73 -lpfaucon,xeMbGBw7j8g,Ga-p11MVYzs,importance,-9,10,2022-06-06,73 -lpfaucon,xeMbGBw7j8g,Ga-p11MVYzs,largely_recommended,-6,10,2022-06-06,73 -lpfaucon,SNx3A0kiLqs,xeMbGBw7j8g,entertaining_relaxing,5,10,2021-09-27,37 -lpfaucon,SNx3A0kiLqs,xeMbGBw7j8g,importance,10,10,2021-09-27,37 -lpfaucon,SNx3A0kiLqs,xeMbGBw7j8g,largely_recommended,10,10,2021-09-27,37 -lpfaucon,P6v4rbgeAiY,xeMbGBw7j8g,entertaining_relaxing,-7,10,2021-10-04,38 -lpfaucon,P6v4rbgeAiY,xeMbGBw7j8g,largely_recommended,7,10,2021-10-04,38 -lpfaucon,P6v4rbgeAiY,xeMbGBw7j8g,importance,7,10,2021-10-04,38 -lpfaucon,7rJxvJOtqSA,xeMbGBw7j8g,entertaining_relaxing,-2,10,2021-10-04,38 -lpfaucon,7rJxvJOtqSA,xeMbGBw7j8g,importance,7,10,2021-10-04,38 -lpfaucon,7rJxvJOtqSA,xeMbGBw7j8g,largely_recommended,3,10,2021-10-04,38 -lpfaucon,xaQJbozY_Is,xeMbGBw7j8g,importance,5,10,2021-10-11,39 -lpfaucon,xaQJbozY_Is,xeMbGBw7j8g,largely_recommended,-1,10,2021-10-11,39 -lpfaucon,xaQJbozY_Is,xeMbGBw7j8g,entertaining_relaxing,-5,10,2021-10-11,39 -lpfaucon,gPIRLQZnRNk,xeMbGBw7j8g,largely_recommended,10,10,2021-11-01,42 -lpfaucon,ptKLwD_qx64,xeMbGBw7j8g,importance,10,10,2021-12-06,47 -lpfaucon,ptKLwD_qx64,xeMbGBw7j8g,largely_recommended,10,10,2021-12-06,47 -lpfaucon,ptKLwD_qx64,xeMbGBw7j8g,entertaining_relaxing,10,10,2021-12-06,47 -lpfaucon,7W1Y2nmOya0,xeMbGBw7j8g,largely_recommended,10,10,2021-12-13,48 -lpfaucon,7W1Y2nmOya0,xeMbGBw7j8g,entertaining_relaxing,3,10,2021-12-13,48 -lpfaucon,7W1Y2nmOya0,xeMbGBw7j8g,importance,10,10,2021-12-13,48 -lpfaucon,giYgMiPUJzY,bp_5Zd-E8VM,largely_recommended,2,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,bp_5Zd-E8VM,importance,5,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,bp_5Zd-E8VM,entertaining_relaxing,-2,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,Wujy7OzvdJk,entertaining_relaxing,-2,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,Wujy7OzvdJk,importance,4,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,Wujy7OzvdJk,largely_recommended,0,10,2022-01-03,51 -lpfaucon,giYgMiPUJzY,EAaBYSO5iAo,largely_recommended,-10,10,2023-04-24,119 -lpfaucon,1tmTy5zax4w,NlJHNrzPvkI,entertaining_relaxing,4,10,2022-01-17,53 -lpfaucon,1tmTy5zax4w,NlJHNrzPvkI,importance,2,10,2022-01-17,53 -lpfaucon,1tmTy5zax4w,NlJHNrzPvkI,largely_recommended,2,10,2022-01-17,53 -lpfaucon,1tmTy5zax4w,leX541Dr2rU,largely_recommended,5,10,2022-01-31,55 -lpfaucon,1tmTy5zax4w,leX541Dr2rU,entertaining_relaxing,3,10,2022-01-31,55 -lpfaucon,1tmTy5zax4w,leX541Dr2rU,importance,5,10,2022-01-31,55 -lpfaucon,CjZVqS0puPg,fksKuXhvWX4,largely_recommended,-2,10,2022-02-21,58 -lpfaucon,CjZVqS0puPg,fksKuXhvWX4,importance,6,10,2022-02-21,58 -lpfaucon,CjZVqS0puPg,fksKuXhvWX4,entertaining_relaxing,-2,10,2022-02-21,58 -lpfaucon,zzRrXJRhjiw,fksKuXhvWX4,largely_recommended,-7,10,2022-02-21,58 -lpfaucon,zzRrXJRhjiw,fksKuXhvWX4,entertaining_relaxing,0,10,2022-02-21,58 -lpfaucon,zzRrXJRhjiw,fksKuXhvWX4,importance,-7,10,2022-02-21,58 -lpfaucon,mKte5W9zmbs,fksKuXhvWX4,importance,5,10,2022-02-28,59 -lpfaucon,mKte5W9zmbs,fksKuXhvWX4,largely_recommended,0,10,2022-02-28,59 -lpfaucon,mKte5W9zmbs,fksKuXhvWX4,entertaining_relaxing,-2,10,2022-02-28,59 -lpfaucon,97JuYPSSldg,LXVa9HCHa_M,largely_recommended,-3,10,2022-03-28,63 -lpfaucon,97JuYPSSldg,LXVa9HCHa_M,entertaining_relaxing,2,10,2022-03-28,63 -lpfaucon,97JuYPSSldg,LXVa9HCHa_M,importance,-3,10,2022-03-28,63 -lpfaucon,YVxJNhR9U4g,url1TFdHlSI,entertaining_relaxing,4,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,url1TFdHlSI,importance,0,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,url1TFdHlSI,largely_recommended,4,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,wTJI_WuZSwE,importance,-5,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,wTJI_WuZSwE,largely_recommended,-5,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,wTJI_WuZSwE,entertaining_relaxing,2,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,uBsarKMce_g,largely_recommended,2,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,uBsarKMce_g,entertaining_relaxing,0,10,2022-06-13,74 -lpfaucon,YVxJNhR9U4g,uBsarKMce_g,importance,5,10,2022-06-13,74 -lpfaucon,DVFCWFw23l4,xeMbGBw7j8g,largely_recommended,10,10,2022-07-04,77 -lpfaucon,DVFCWFw23l4,xeMbGBw7j8g,importance,10,10,2022-07-04,77 -lpfaucon,DVFCWFw23l4,xeMbGBw7j8g,entertaining_relaxing,6,10,2022-07-04,77 -lpfaucon,zlqp9eXerfI,LXVa9HCHa_M,largely_recommended,-2,10,2022-07-04,77 -lpfaucon,zlqp9eXerfI,LXVa9HCHa_M,importance,-8,10,2022-07-04,77 -lpfaucon,zlqp9eXerfI,LXVa9HCHa_M,entertaining_relaxing,4,10,2022-07-04,77 -lpfaucon,xmLY7jL-MvE,XRk2VeL0icU,largely_recommended,4,10,2022-08-08,82 -lpfaucon,xmLY7jL-MvE,XRk2VeL0icU,importance,7,10,2022-08-08,82 -lpfaucon,xmLY7jL-MvE,XRk2VeL0icU,entertaining_relaxing,10,10,2022-08-08,82 -lpfaucon,EFUYNoFRHQI,LXVa9HCHa_M,entertaining_relaxing,2,10,2022-08-29,85 -lpfaucon,EFUYNoFRHQI,LXVa9HCHa_M,importance,2,10,2022-08-29,85 -lpfaucon,EFUYNoFRHQI,LXVa9HCHa_M,largely_recommended,2,10,2022-08-29,85 -lpfaucon,f1dnocPQXDQ,LXVa9HCHa_M,largely_recommended,-2,10,2022-08-29,85 -lpfaucon,f1dnocPQXDQ,LXVa9HCHa_M,importance,3,10,2022-08-29,85 -lpfaucon,f1dnocPQXDQ,LXVa9HCHa_M,entertaining_relaxing,-6,10,2022-08-29,85 -lpfaucon,TBhfT2kA2iQ,ONRzXHhBMuY,entertaining_relaxing,10,10,2022-10-10,91 -lpfaucon,TBhfT2kA2iQ,ONRzXHhBMuY,importance,-3,10,2022-10-10,91 -lpfaucon,TBhfT2kA2iQ,ONRzXHhBMuY,largely_recommended,2,10,2022-10-10,91 -lpfaucon,BnP9AbA_kBU,ONRzXHhBMuY,largely_recommended,-2,10,2022-10-10,91 -lpfaucon,BnP9AbA_kBU,ONRzXHhBMuY,entertaining_relaxing,3,10,2022-10-10,91 -lpfaucon,BnP9AbA_kBU,ONRzXHhBMuY,importance,-4,10,2022-10-10,91 -lpfaucon,zN813nD9cWA,ONRzXHhBMuY,largely_recommended,2,10,2022-10-10,91 -lpfaucon,zN813nD9cWA,ONRzXHhBMuY,entertaining_relaxing,-10,10,2022-10-10,91 -lpfaucon,zN813nD9cWA,ONRzXHhBMuY,importance,9,10,2022-10-10,91 -lpfaucon,fSwpe8r50_o,ONRzXHhBMuY,importance,4,10,2022-10-10,91 -lpfaucon,fSwpe8r50_o,ONRzXHhBMuY,entertaining_relaxing,-5,10,2022-10-10,91 -lpfaucon,fSwpe8r50_o,ONRzXHhBMuY,largely_recommended,-2,10,2022-10-10,91 -lpfaucon,rvskMHn0sqQ,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -lpfaucon,rvskMHn0sqQ,BDQX_Whx--E,importance,0,10,2022-10-24,93 -lpfaucon,rvskMHn0sqQ,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,J5LodnKnLYU,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -lpfaucon,J5LodnKnLYU,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,J5LodnKnLYU,BDQX_Whx--E,importance,0,10,2022-10-24,93 -lpfaucon,2wXjSyoWmeg,BDQX_Whx--E,importance,0,10,2022-10-24,93 -lpfaucon,2wXjSyoWmeg,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,2wXjSyoWmeg,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -lpfaucon,GNmp_T2OWfk,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,GNmp_T2OWfk,BDQX_Whx--E,importance,0,10,2022-10-24,93 -lpfaucon,GNmp_T2OWfk,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -lpfaucon,IYblisCkLiw,BDQX_Whx--E,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,IYblisCkLiw,BDQX_Whx--E,importance,0,10,2022-10-24,93 -lpfaucon,IYblisCkLiw,BDQX_Whx--E,largely_recommended,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,KOZXFn3P_AE,largely_recommended,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,KOZXFn3P_AE,importance,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,KOZXFn3P_AE,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,rFGjqet5o2c,largely_recommended,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,rFGjqet5o2c,importance,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,rFGjqet5o2c,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,ZzH-bAY6KGI,largely_recommended,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,ZzH-bAY6KGI,entertaining_relaxing,0,10,2022-10-24,93 -lpfaucon,BDQX_Whx--E,ZzH-bAY6KGI,importance,0,10,2022-10-24,93 -lpfaucon,GvfoDg5O9bI,xeMbGBw7j8g,entertaining_relaxing,4,10,2022-10-24,93 -lpfaucon,GvfoDg5O9bI,xeMbGBw7j8g,importance,8,10,2022-10-24,93 -lpfaucon,GvfoDg5O9bI,xeMbGBw7j8g,largely_recommended,5,10,2022-10-24,93 -lpfaucon,46QRfChKDgg,rd6Z0HQenuM,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,rd6Z0HQenuM,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,rd6Z0HQenuM,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,QT-oDKHn-Fo,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,QT-oDKHn-Fo,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,QT-oDKHn-Fo,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,u148ZVqBBgY,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,u148ZVqBBgY,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,u148ZVqBBgY,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,9gPv4qzzb9Q,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,9gPv4qzzb9Q,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,9gPv4qzzb9Q,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,YW3rHvMh5AE,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,YW3rHvMh5AE,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,YW3rHvMh5AE,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,hCQ_qvxcf_o,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,hCQ_qvxcf_o,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,hCQ_qvxcf_o,importance,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,xaQJbozY_Is,entertaining_relaxing,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,xaQJbozY_Is,largely_recommended,0,10,2022-11-28,98 -lpfaucon,46QRfChKDgg,xaQJbozY_Is,importance,0,10,2022-11-28,98 -lpfaucon,uljTEmmCh_E,K9UE2WD6nu8,importance,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,K9UE2WD6nu8,largely_recommended,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,K9UE2WD6nu8,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,7WGaMAb-ivs,largely_recommended,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,7WGaMAb-ivs,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,7WGaMAb-ivs,importance,0,10,2023-01-23,106 -lpfaucon,uljTEmmCh_E,uYYRAPBbr_w,largely_recommended,0,10,2023-02-27,111 -lpfaucon,uljTEmmCh_E,uYYRAPBbr_w,entertaining_relaxing,0,10,2023-02-27,111 -lpfaucon,uljTEmmCh_E,uYYRAPBbr_w,importance,0,10,2023-02-27,111 -lpfaucon,bAn5zcG8-HA,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -lpfaucon,bAn5zcG8-HA,uljTEmmCh_E,importance,0,10,2023-01-23,106 -lpfaucon,bAn5zcG8-HA,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,9BBqFZwBsgs,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,9BBqFZwBsgs,uljTEmmCh_E,importance,0,10,2023-01-23,106 -lpfaucon,9BBqFZwBsgs,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -lpfaucon,d35JQvaEen0,uljTEmmCh_E,importance,0,10,2023-01-23,106 -lpfaucon,d35JQvaEen0,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -lpfaucon,d35JQvaEen0,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,JXeJANDKwDc,uljTEmmCh_E,largely_recommended,0,10,2023-01-23,106 -lpfaucon,JXeJANDKwDc,uljTEmmCh_E,entertaining_relaxing,0,10,2023-01-23,106 -lpfaucon,JXeJANDKwDc,uljTEmmCh_E,importance,0,10,2023-01-23,106 -lpfaucon,GWtQN2v4yzk,jfv9zsKJquk,largely_recommended,10,10,2023-02-13,109 -lpfaucon,GWtQN2v4yzk,Et9Nf-rsALk,largely_recommended,10,10,2023-02-13,109 -lpfaucon,GWtQN2v4yzk,wO2lWmgEK1Y,largely_recommended,10,10,2023-02-13,109 -lpfaucon,GWtQN2v4yzk,Rhnng_u5ZnU,largely_recommended,0,10,2023-02-13,109 -lpfaucon,GWtQN2v4yzk,s4lF9ExiR8s,largely_recommended,0,10,2023-05-15,122 -lpfaucon,GWtQN2v4yzk,2ziB-7nWeQo,largely_recommended,0,10,2023-05-15,122 -lpfaucon,GWtQN2v4yzk,kxV8mkfzYrI,largely_recommended,0,10,2023-05-15,122 -lpfaucon,a4tbf-ftbds,OK7czUnuXac,entertaining_relaxing,4,10,2023-02-27,111 -lpfaucon,a4tbf-ftbds,OK7czUnuXac,importance,-5,10,2023-02-27,111 -lpfaucon,a4tbf-ftbds,OK7czUnuXac,largely_recommended,-1,10,2023-02-27,111 -lpfaucon,CHoXZO7WFDA,OK7czUnuXac,largely_recommended,-8,10,2023-02-27,111 -lpfaucon,CHoXZO7WFDA,OK7czUnuXac,entertaining_relaxing,-4,10,2023-02-27,111 -lpfaucon,CHoXZO7WFDA,OK7czUnuXac,importance,-8,10,2023-02-27,111 -lpfaucon,f3xH9QNxPzs,OK7czUnuXac,largely_recommended,10,10,2023-02-27,111 -lpfaucon,qSyyF4Nla5M,V6ChTqII-Yk,largely_recommended,4,10,2023-03-13,113 -lpfaucon,qSyyF4Nla5M,V6ChTqII-Yk,entertaining_relaxing,2,10,2023-03-13,113 -lpfaucon,qSyyF4Nla5M,V6ChTqII-Yk,importance,4,10,2023-03-13,113 -lpfaucon,YqPYDWPYXFs,V6ChTqII-Yk,largely_recommended,10,10,2023-03-13,113 -lpfaucon,O02n7ZF5D8g,1tmTy5zax4w,largely_recommended,4,10,2023-04-03,116 -lpfaucon,BHMF-FlkqPw,4ZX9T0kWb4Y,largely_recommended,-4,10,2023-04-10,117 -lpfaucon,GgyX-MnRAuY,4ZX9T0kWb4Y,largely_recommended,-4,10,2023-04-10,117 -lpfaucon,qGH_D8FazPc,4ZX9T0kWb4Y,largely_recommended,4,10,2023-04-10,117 -lpfaucon,ZYDN25N5WhQ,4ZX9T0kWb4Y,largely_recommended,4,10,2023-04-10,117 -lpfaucon,ka1G2IM5EN4,V6ChTqII-Yk,largely_recommended,10,10,2023-04-10,117 -lpfaucon,sUQQWuftklk,1tmTy5zax4w,largely_recommended,10,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,ljH3--iTeBI,importance,-5,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,ljH3--iTeBI,entertaining_relaxing,2,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,ljH3--iTeBI,largely_recommended,-8,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,9DcV13a9hVg,largely_recommended,-8,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,kbAbh-jvpJg,entertaining_relaxing,4,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,kbAbh-jvpJg,importance,0,10,2023-05-01,120 -lpfaucon,7dkDxmZPWD4,kbAbh-jvpJg,largely_recommended,-10,10,2023-05-01,120 -lpfaucon,HOdqEmQpygA,BDQX_Whx--E,largely_recommended,10,10,2023-05-08,121 -lpfaucon,EzkuQ2N2DS8,GWtQN2v4yzk,largely_recommended,0,10,2023-05-15,122 -lpfaucon,MPupR1YaOC8,GWtQN2v4yzk,largely_recommended,0,10,2023-05-15,122 -lpfaucon,995W3WHrQHg,GWtQN2v4yzk,largely_recommended,0,10,2023-05-15,122 -lpfaucon,jIHRAVq8IB4,r6yLdZMrjl8,entertaining_relaxing,2,10,2023-06-05,125 -lpfaucon,jIHRAVq8IB4,r6yLdZMrjl8,importance,-2,10,2023-06-05,125 -lpfaucon,jIHRAVq8IB4,r6yLdZMrjl8,largely_recommended,-6,10,2023-06-05,125 -lpfaucon,E8YuCjwVZLw,r6yLdZMrjl8,largely_recommended,-10,10,2023-06-05,125 -lpfaucon,42QuXLucH3Q,r6yLdZMrjl8,largely_recommended,-10,10,2023-06-05,125 -lpfaucon,JiiZ2DJLge8,r6yLdZMrjl8,largely_recommended,-3,10,2023-06-05,125 -lpfaucon,JiiZ2DJLge8,r6yLdZMrjl8,importance,5,10,2023-06-05,125 -lpfaucon,JiiZ2DJLge8,r6yLdZMrjl8,entertaining_relaxing,-3,10,2023-06-05,125 -lpfaucon,_4ICxLCJczI,fksKuXhvWX4,entertaining_relaxing,-2,10,2023-06-26,128 -lpfaucon,_4ICxLCJczI,fksKuXhvWX4,importance,-2,10,2023-06-26,128 -lpfaucon,_4ICxLCJczI,fksKuXhvWX4,largely_recommended,-2,10,2023-06-26,128 -lpfaucon,MFnOaaXwOJk,oAMM3l156Oo,importance,10,10,2023-06-26,128 -lpfaucon,MFnOaaXwOJk,oAMM3l156Oo,entertaining_relaxing,-2,10,2023-06-26,128 -lpfaucon,MFnOaaXwOJk,oAMM3l156Oo,largely_recommended,5,10,2023-06-26,128 -lpfaucon,XQi6aO2CSgY,oAMM3l156Oo,entertaining_relaxing,3,10,2023-06-26,128 -lpfaucon,XQi6aO2CSgY,oAMM3l156Oo,importance,-5,10,2023-06-26,128 -lpfaucon,XQi6aO2CSgY,oAMM3l156Oo,largely_recommended,-3,10,2023-06-26,128 -lpfaucon,37oYeiYJGOM,oAMM3l156Oo,importance,10,10,2023-06-26,128 -lpfaucon,37oYeiYJGOM,oAMM3l156Oo,largely_recommended,10,10,2023-06-26,128 -lpfaucon,37oYeiYJGOM,oAMM3l156Oo,entertaining_relaxing,-10,10,2023-06-26,128 -lpfaucon,YC-v3whLUX0,oAMM3l156Oo,largely_recommended,-5,10,2023-06-26,128 -lpfaucon,YC-v3whLUX0,oAMM3l156Oo,entertaining_relaxing,-1,10,2023-06-26,128 -lpfaucon,YC-v3whLUX0,oAMM3l156Oo,importance,-5,10,2023-06-26,128 -lpfaucon,PRz54V7rU4U,oAMM3l156Oo,entertaining_relaxing,-2,10,2023-06-26,128 -lpfaucon,PRz54V7rU4U,oAMM3l156Oo,importance,-5,10,2023-06-26,128 -lpfaucon,PRz54V7rU4U,oAMM3l156Oo,largely_recommended,-2,10,2023-06-26,128 -lpfaucon,the81FQoAUI,oAMM3l156Oo,largely_recommended,-2,10,2023-06-26,128 -lpfaucon,the81FQoAUI,oAMM3l156Oo,entertaining_relaxing,-2,10,2023-06-26,128 -lpfaucon,the81FQoAUI,oAMM3l156Oo,importance,-2,10,2023-06-26,128 -lpfaucon,mI8b8Zjq8-Y,oAMM3l156Oo,entertaining_relaxing,-8,10,2023-06-26,128 -lpfaucon,mI8b8Zjq8-Y,oAMM3l156Oo,largely_recommended,10,10,2023-06-26,128 -lpfaucon,mI8b8Zjq8-Y,oAMM3l156Oo,importance,10,10,2023-06-26,128 -lpfaucon,Dfgl3Ii3lb8,7dkDxmZPWD4,entertaining_relaxing,5,10,2023-07-03,129 -lpfaucon,Dfgl3Ii3lb8,7dkDxmZPWD4,largely_recommended,10,10,2023-07-03,129 -lpfaucon,Dfgl3Ii3lb8,7dkDxmZPWD4,importance,10,10,2023-07-03,129 -lpfaucon,-qJIhEhZmYw,U_r8O1Henao,largely_recommended,2,10,2023-07-10,130 -lpfaucon,-qJIhEhZmYw,U_r8O1Henao,importance,0,10,2023-07-10,130 -lpfaucon,-qJIhEhZmYw,U_r8O1Henao,entertaining_relaxing,2,10,2023-07-10,130 -lpfaucon,ukj00RbvZaQ,U_r8O1Henao,largely_recommended,7,10,2023-07-10,130 -lpfaucon,ukj00RbvZaQ,U_r8O1Henao,entertaining_relaxing,-3,10,2023-07-10,130 -lpfaucon,ukj00RbvZaQ,U_r8O1Henao,importance,7,10,2023-07-10,130 -lpfaucon,wV0AhYEfNa8,U_r8O1Henao,importance,7,10,2023-07-10,130 -lpfaucon,wV0AhYEfNa8,U_r8O1Henao,largely_recommended,7,10,2023-07-10,130 -lpfaucon,wV0AhYEfNa8,U_r8O1Henao,entertaining_relaxing,-5,10,2023-07-10,130 -lpfaucon,VBoc6dQKmTo,V6ChTqII-Yk,entertaining_relaxing,6,10,2023-07-24,132 -lpfaucon,VBoc6dQKmTo,V6ChTqII-Yk,largely_recommended,2,10,2023-07-24,132 -lpfaucon,VBoc6dQKmTo,V6ChTqII-Yk,importance,0,10,2023-07-24,132 -lpfaucon,iGGOjD_OtAM,hRAFPdDppzs,largely_recommended,-4,10,2023-08-21,136 -lpfaucon,DOahTUU4nso,hRAFPdDppzs,largely_recommended,10,10,2023-08-21,136 -lpfaucon,56C4Z1eZH4E,izVUMXAZNA0,largely_recommended,0,10,2023-08-21,136 -lpfaucon,56C4Z1eZH4E,izVUMXAZNA0,importance,0,10,2023-08-21,136 -lpfaucon,56C4Z1eZH4E,izVUMXAZNA0,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,M2-I4Ewy40U,izVUMXAZNA0,importance,0,10,2023-08-21,136 -lpfaucon,M2-I4Ewy40U,izVUMXAZNA0,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,M2-I4Ewy40U,izVUMXAZNA0,largely_recommended,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,2wfgrujnBwg,importance,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,2wfgrujnBwg,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,2wfgrujnBwg,largely_recommended,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,Rbz_i1MKqYA,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,Rbz_i1MKqYA,importance,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,Rbz_i1MKqYA,largely_recommended,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,_-QaP5zYWdI,largely_recommended,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,_-QaP5zYWdI,importance,0,10,2023-08-21,136 -lpfaucon,izVUMXAZNA0,_-QaP5zYWdI,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,Tvr6F6CZuGU,izVUMXAZNA0,largely_recommended,0,10,2023-08-21,136 -lpfaucon,Tvr6F6CZuGU,izVUMXAZNA0,importance,0,10,2023-08-21,136 -lpfaucon,Tvr6F6CZuGU,izVUMXAZNA0,entertaining_relaxing,0,10,2023-08-21,136 -lpfaucon,f0e-Soo1qFQ,izVUMXAZNA0,entertaining_relaxing,-10,10,2023-08-21,136 -lpfaucon,f0e-Soo1qFQ,izVUMXAZNA0,importance,-10,10,2023-08-21,136 -lpfaucon,f0e-Soo1qFQ,izVUMXAZNA0,largely_recommended,-10,10,2023-08-21,136 -lpfaucon,KRghdvCMWM4,izVUMXAZNA0,entertaining_relaxing,-10,10,2023-08-21,136 -lpfaucon,KRghdvCMWM4,izVUMXAZNA0,importance,-5,10,2023-08-21,136 -lpfaucon,KRghdvCMWM4,izVUMXAZNA0,largely_recommended,-10,10,2023-08-21,136 -lpfaucon,hRAFPdDppzs,JYHIrngDvK0,largely_recommended,-10,10,2023-08-28,137 -lpfaucon,hRAFPdDppzs,JYHIrngDvK0,importance,-10,10,2023-08-28,137 -lpfaucon,hRAFPdDppzs,JYHIrngDvK0,entertaining_relaxing,-10,10,2023-08-28,137 -lpfaucon,hRAFPdDppzs,kSLzSvNR6xc,largely_recommended,-5,10,2023-08-28,137 -lpfaucon,EYEezy9rej8,izVUMXAZNA0,importance,0,10,2023-09-11,139 -lpfaucon,EYEezy9rej8,izVUMXAZNA0,largely_recommended,0,10,2023-09-11,139 -lpfaucon,EYEezy9rej8,izVUMXAZNA0,entertaining_relaxing,0,10,2023-09-11,139 -lpfaucon,QaDilpBgqFk,r6yLdZMrjl8,largely_recommended,10,10,2023-09-11,139 -lpfaucon,QaDilpBgqFk,r6yLdZMrjl8,entertaining_relaxing,10,10,2023-09-11,139 -lpfaucon,QaDilpBgqFk,r6yLdZMrjl8,importance,10,10,2023-09-11,139 -lpfaucon,Y7daihE0D_8,4ZX9T0kWb4Y,largely_recommended,10,10,2023-09-11,139 -lpfaucon,Y7daihE0D_8,4ZX9T0kWb4Y,importance,10,10,2023-09-11,139 -lpfaucon,Y7daihE0D_8,4ZX9T0kWb4Y,entertaining_relaxing,10,10,2023-09-11,139 -lpfaucon,OT5BNd_2Vv4,GWtQN2v4yzk,largely_recommended,0,10,2023-09-11,139 -lpfaucon,OT5BNd_2Vv4,GWtQN2v4yzk,entertaining_relaxing,0,10,2023-09-11,139 -lpfaucon,OT5BNd_2Vv4,GWtQN2v4yzk,importance,0,10,2023-09-11,139 -lpfaucon,F9TPGy1P2Sc,GWtQN2v4yzk,largely_recommended,0,10,2023-09-11,139 -lpfaucon,F9TPGy1P2Sc,GWtQN2v4yzk,importance,0,10,2023-09-11,139 -lpfaucon,F9TPGy1P2Sc,GWtQN2v4yzk,entertaining_relaxing,0,10,2023-09-11,139 -lpfaucon,nR2YJN4OEL4,BgO25FTwfRI,largely_recommended,-2,10,2023-09-11,139 -lpfaucon,nR2YJN4OEL4,BgO25FTwfRI,entertaining_relaxing,0,10,2023-09-11,139 -lpfaucon,nR2YJN4OEL4,gc5uPnlI0U0,entertaining_relaxing,-6,10,2023-09-11,139 -lpfaucon,nR2YJN4OEL4,gc5uPnlI0U0,largely_recommended,-2,10,2023-09-11,139 -lpfaucon,zZrmp5xNcuY,DqhXsEgLMJ0,largely_recommended,-1,10,2023-09-11,139 -lpfaucon,zZrmp5xNcuY,DqhXsEgLMJ0,entertaining_relaxing,-1,10,2023-09-11,139 -lpfaucon,rQDbhodjrsI,DqhXsEgLMJ0,largely_recommended,-3,10,2023-09-18,140 -lpfaucon,rQDbhodjrsI,DqhXsEgLMJ0,entertaining_relaxing,-3,10,2023-09-18,140 -lpfaucon,rQDbhodjrsI,nR2YJN4OEL4,entertaining_relaxing,3,10,2023-09-18,140 -lpfaucon,rQDbhodjrsI,nR2YJN4OEL4,largely_recommended,3,10,2023-09-18,140 -lpfaucon,awnotG4dJy8,4ZX9T0kWb4Y,largely_recommended,10,10,2023-09-18,140 -lpfaucon,awnotG4dJy8,4ZX9T0kWb4Y,importance,10,10,2023-09-18,140 -lpfaucon,awnotG4dJy8,4ZX9T0kWb4Y,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,YipjRkar_Dw,izVUMXAZNA0,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,YipjRkar_Dw,izVUMXAZNA0,largely_recommended,0,10,2023-09-18,140 -lpfaucon,YipjRkar_Dw,izVUMXAZNA0,importance,0,10,2023-09-18,140 -lpfaucon,-oE0tBF7jic,GWtQN2v4yzk,largely_recommended,0,10,2023-09-18,140 -lpfaucon,-oE0tBF7jic,GWtQN2v4yzk,importance,0,10,2023-09-18,140 -lpfaucon,-oE0tBF7jic,GWtQN2v4yzk,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,w_-NNleCw64,BDQX_Whx--E,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,w_-NNleCw64,BDQX_Whx--E,largely_recommended,10,10,2023-09-18,140 -lpfaucon,w_-NNleCw64,BDQX_Whx--E,importance,10,10,2023-09-18,140 -lpfaucon,cdqcNOPT8Cg,izVUMXAZNA0,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,cdqcNOPT8Cg,izVUMXAZNA0,importance,0,10,2023-09-18,140 -lpfaucon,cdqcNOPT8Cg,izVUMXAZNA0,largely_recommended,0,10,2023-09-18,140 -lpfaucon,8zP01ArSksA,GWtQN2v4yzk,importance,0,10,2023-09-18,140 -lpfaucon,8zP01ArSksA,GWtQN2v4yzk,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,8zP01ArSksA,GWtQN2v4yzk,largely_recommended,0,10,2023-09-18,140 -lpfaucon,5CRI6KA8bgA,nR2YJN4OEL4,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,5CRI6KA8bgA,nR2YJN4OEL4,largely_recommended,10,10,2023-09-18,140 -lpfaucon,5CRI6KA8bgA,nR2YJN4OEL4,importance,10,10,2023-09-18,140 -lpfaucon,HQh06Co2scY,GWtQN2v4yzk,largely_recommended,0,10,2023-09-18,140 -lpfaucon,HQh06Co2scY,GWtQN2v4yzk,importance,0,10,2023-09-18,140 -lpfaucon,HQh06Co2scY,GWtQN2v4yzk,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,upe9RLnPY6k,7dkDxmZPWD4,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,upe9RLnPY6k,7dkDxmZPWD4,importance,10,10,2023-09-18,140 -lpfaucon,upe9RLnPY6k,7dkDxmZPWD4,largely_recommended,10,10,2023-09-18,140 -lpfaucon,KwUr6wqeVT0,IS7vz55_IS0,importance,0,10,2023-09-18,140 -lpfaucon,KwUr6wqeVT0,IS7vz55_IS0,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,KwUr6wqeVT0,IS7vz55_IS0,largely_recommended,0,10,2023-09-18,140 -lpfaucon,oaubV-mYNhQ,izVUMXAZNA0,importance,0,10,2023-09-18,140 -lpfaucon,oaubV-mYNhQ,izVUMXAZNA0,largely_recommended,0,10,2023-09-18,140 -lpfaucon,oaubV-mYNhQ,izVUMXAZNA0,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,d-M0mqSFoOw,largely_recommended,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,d-M0mqSFoOw,importance,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,d-M0mqSFoOw,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,BlA0SSjaXnY,largely_recommended,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,BlA0SSjaXnY,importance,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,BlA0SSjaXnY,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,_z11PNOSbnM,largely_recommended,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,_z11PNOSbnM,importance,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,_z11PNOSbnM,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,EYEezy9rej8,importance,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,EYEezy9rej8,largely_recommended,0,10,2023-09-18,140 -lpfaucon,pUYXZK7ZWHg,EYEezy9rej8,entertaining_relaxing,0,10,2023-09-18,140 -lpfaucon,kJiw36B64Ns,hRAFPdDppzs,largely_recommended,10,10,2023-09-18,140 -lpfaucon,kJiw36B64Ns,hRAFPdDppzs,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,kJiw36B64Ns,hRAFPdDppzs,importance,10,10,2023-09-18,140 -lpfaucon,JSI6SfenqTA,ONRzXHhBMuY,largely_recommended,10,10,2023-09-18,140 -lpfaucon,JSI6SfenqTA,ONRzXHhBMuY,importance,10,10,2023-09-18,140 -lpfaucon,JSI6SfenqTA,ONRzXHhBMuY,entertaining_relaxing,10,10,2023-09-18,140 -lpfaucon,HEUuSP3lKIQ,FPZONhA0C60,largely_recommended,-4,10,2023-10-02,142 -lpfaucon,LyNBSPwejtY,FPZONhA0C60,largely_recommended,-2,10,2023-10-02,142 -lpfaucon,GfiOkCdDKws,FPZONhA0C60,largely_recommended,-4,10,2023-10-02,142 -lpfaucon,PvFy2TuPDaw,FPZONhA0C60,largely_recommended,-10,10,2023-10-02,142 -lpfaucon,mRrRERFFhJQ,DqhXsEgLMJ0,largely_recommended,5,10,2023-10-02,142 -lpfaucon,OS6gzabM0pI,Hbrh7KOyuRY,largely_recommended,8,10,2023-10-16,144 -lpfaucon,OS6gzabM0pI,5eHolA0GBkM,largely_recommended,10,10,2023-10-16,144 -lpfaucon,CtD0_cl2ZlA,RoTJzu548W4,importance,-10,10,2024-01-08,156 -lpfaucon,CtD0_cl2ZlA,RoTJzu548W4,largely_recommended,2,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,7DKv5H5Frt0,importance,5,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,7DKv5H5Frt0,largely_recommended,10,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,7Nw6qyyrTeI,importance,10,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,7Nw6qyyrTeI,largely_recommended,10,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,xjw-TND-Vss,importance,0,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,xjw-TND-Vss,largely_recommended,0,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,rFv8j9qomWc,importance,10,10,2024-01-08,156 -lpfaucon,g7ih6rHdw3M,rFv8j9qomWc,largely_recommended,10,10,2024-01-08,156 -lpfaucon,PY3Qe_b9ufI,CtD0_cl2ZlA,entertaining_relaxing,-8,10,2024-01-29,159 -lpfaucon,PY3Qe_b9ufI,CtD0_cl2ZlA,largely_recommended,-6,10,2024-01-29,159 -lpfaucon,N_ayq66t77U,OS6gzabM0pI,largely_recommended,-10,10,2024-01-29,159 -lpfaucon,N_ayq66t77U,OS6gzabM0pI,entertaining_relaxing,-8,10,2024-01-29,159 -lpfaucon,kB14QIKcR5k,J6taUGrJT-w,largely_recommended,-6,10,2024-02-19,162 -lpfaucon,kB14QIKcR5k,J6taUGrJT-w,entertaining_relaxing,-6,10,2024-02-19,162 -lpfaucon,C_R9CBda7vY,IjSdrg5Bq3w,entertaining_relaxing,3,10,2024-02-19,162 -lpfaucon,C_R9CBda7vY,IjSdrg5Bq3w,largely_recommended,10,10,2024-02-19,162 -lpfaucon,C_R9CBda7vY,2t6oGDIBZSE,entertaining_relaxing,10,10,2024-04-08,169 -lpfaucon,C_R9CBda7vY,2t6oGDIBZSE,largely_recommended,8,10,2024-04-08,169 -lpfaucon,UfzrF6Vwcy8,C_R9CBda7vY,largely_recommended,-3,10,2024-02-19,162 -lpfaucon,UfzrF6Vwcy8,C_R9CBda7vY,entertaining_relaxing,-3,10,2024-02-19,162 -lpfaucon,3XSG2Dw2mL8,J6taUGrJT-w,largely_recommended,-10,10,2024-02-26,163 -lpfaucon,a4Yfz2FxXiY,louadb5ZTx4,largely_recommended,10,10,2024-03-04,164 -lpfaucon,a4Yfz2FxXiY,7wwbqH1A-4w,largely_recommended,10,10,2024-03-04,164 -lpfaucon,aIp-aa8F9EI,Tf0NKBvEeKk,largely_recommended,-3,10,2024-03-04,164 -lpfaucon,sBfUwV4vCWg,aIp-aa8F9EI,largely_recommended,-1,10,2024-03-04,164 -lpfaucon,k3bkNewAR5U,YeFQRLbOyTw,largely_recommended,-10,10,2024-03-04,164 -lpfaucon,Q8oCilY4szc,k3bkNewAR5U,largely_recommended,0,10,2024-03-11,165 -lpfaucon,egVO61490h8,aIp-aa8F9EI,largely_recommended,10,10,2024-03-11,165 -lpfaucon,7Go9qIxotkk,k3bkNewAR5U,largely_recommended,10,10,2024-03-25,167 -lpfaucon,l1wpuxgutSU,a4Yfz2FxXiY,largely_recommended,-5,10,2024-03-25,167 -lpfaucon,gBr6Oddtgiw,Oi5Cp7YALXw,largely_recommended,10,10,2024-04-08,169 -lpfaucon,gBr6Oddtgiw,zwJ-xK7gJ9s,largely_recommended,10,10,2024-04-08,169 -lpfaucon,CGIEjak1xfs,eMlx5fFNoYc,entertaining_relaxing,4,10,2024-05-13,174 -lpfaucon,CGIEjak1xfs,eMlx5fFNoYc,largely_recommended,8,10,2024-05-13,174 -lpfaucon,CGIEjak1xfs,WjsXFY_tGx4,importance,0,10,2024-05-27,176 -lpfaucon,CGIEjak1xfs,WjsXFY_tGx4,largely_recommended,0,10,2024-05-27,176 -lpfaucon,CGIEjak1xfs,WjsXFY_tGx4,entertaining_relaxing,10,10,2024-05-27,176 -lpfaucon,YUMtJ6K43K8,KygUNB4LHbM,entertaining_relaxing,0,10,2024-05-20,175 -lpfaucon,YUMtJ6K43K8,KygUNB4LHbM,largely_recommended,10,10,2024-05-20,175 -lpfaucon,Rl4h3IeOuY8,KygUNB4LHbM,entertaining_relaxing,-6,10,2024-05-20,175 -lpfaucon,Rl4h3IeOuY8,KygUNB4LHbM,largely_recommended,0,10,2024-05-20,175 -lpfaucon,Jtmo3T98eQw,gBr6Oddtgiw,importance,-7,10,2024-05-27,176 -lpfaucon,Jtmo3T98eQw,gBr6Oddtgiw,entertaining_relaxing,7,10,2024-05-27,176 -lpfaucon,Jtmo3T98eQw,gBr6Oddtgiw,largely_recommended,-7,10,2024-05-27,176 -lpfaucon,KygUNB4LHbM,zL7eHC6WfyA,largely_recommended,-10,10,2024-05-27,176 -lpfaucon,v5ev-RAg7Xs,BnEgnrUCXPY,largely_recommended,-10,10,2024-06-10,178 -lpfaucon,v5ev-RAg7Xs,VMj-3S1tku0,largely_recommended,-10,10,2024-06-10,178 -lpfaucon,v5ev-RAg7Xs,H71WR50stm4,largely_recommended,10,10,2024-06-10,178 -lpfaucon,zWPe_CUR4yU,JEEOcwOAKng,largely_recommended,10,10,2024-07-29,185 -lpfaucon,zWPe_CUR4yU,6E8VE6fZQoo,largely_recommended,10,10,2024-07-29,185 -lpfaucon,zWPe_CUR4yU,J9k-22Lv9bU,largely_recommended,10,10,2024-07-29,185 -lpfaucon,zWPe_CUR4yU,5iPH-br_eJQ,largely_recommended,10,10,2024-07-29,185 -lpfaucon,SnJ6Ttaiu9M,68zOvCLwcL8,largely_recommended,-10,10,2024-09-09,191 -lpfaucon,o-6TmHdW7uM,68zOvCLwcL8,largely_recommended,-8,10,2024-09-16,192 -lpfaucon,7J44j6Fw8NM,v5ev-RAg7Xs,largely_recommended,5,10,2024-09-16,192 -lpfaucon,MmOYmPM7OFE,kyNQ5YoFkWo,largely_recommended,-10,10,2024-09-16,192 -lpfaucon,MmOYmPM7OFE,Y4hcZN-uXU8,largely_recommended,-7,10,2024-09-16,192 -lpfaucon,5GFGTuCONJc,Iy2FieTWWZ8,largely_recommended,10,10,2024-10-14,196 -lpfaucon,5GFGTuCONJc,3brE46isq5A,largely_recommended,10,10,2024-10-14,196 -lpfaucon,5GFGTuCONJc,6B2-5NI9sDU,largely_recommended,10,10,2024-10-14,196 -lpfaucon,5GFGTuCONJc,gQPYNAYRokw,largely_recommended,10,10,2024-10-14,196 -lpfaucon,ZP7T6WAK3Ow,MD_CMrCpBMc,largely_recommended,-5,10,2024-10-14,196 -lpfaucon,ZP7T6WAK3Ow,c066hLi78B0,largely_recommended,-10,10,2024-10-14,196 -lpfaucon,J6taUGrJT-w,UMofZIT9FcQ,largely_recommended,10,10,2024-10-28,198 -lpfaucon,UBVV8pch1dM,CtD0_cl2ZlA,largely_recommended,0,2,2024-11-25,202 -NatNgs,tmLznjLR18A,EcYcIAaTeRA,entertaining_relaxing,6,10,2023-01-23,106 -NatNgs,tmLznjLR18A,EcYcIAaTeRA,importance,-2,10,2023-01-23,106 -NatNgs,tmLznjLR18A,EcYcIAaTeRA,largely_recommended,3,10,2023-01-23,106 -NatNgs,qVZhwYupcg4,EcYcIAaTeRA,largely_recommended,-3,10,2023-01-23,106 -NatNgs,qVZhwYupcg4,EcYcIAaTeRA,entertaining_relaxing,-3,10,2023-01-23,106 -NatNgs,qVZhwYupcg4,EcYcIAaTeRA,importance,0,10,2023-01-23,106 -NatNgs,yqVOC_4dsZA,EcYcIAaTeRA,largely_recommended,-2,10,2023-01-23,106 -NatNgs,yqVOC_4dsZA,EcYcIAaTeRA,importance,1,10,2023-01-23,106 -NatNgs,yqVOC_4dsZA,EcYcIAaTeRA,entertaining_relaxing,2,10,2023-01-23,106 -NatNgs,MrzDPQFG57w,EcYcIAaTeRA,entertaining_relaxing,4,10,2023-01-23,106 -NatNgs,MrzDPQFG57w,EcYcIAaTeRA,importance,2,10,2023-01-23,106 -NatNgs,MrzDPQFG57w,EcYcIAaTeRA,largely_recommended,-8,10,2023-01-23,106 -NatNgs,MrzDPQFG57w,q4xZArgOIWc,largely_recommended,-4,10,2023-09-04,138 -NatNgs,MrzDPQFG57w,q4xZArgOIWc,importance,-3,10,2023-09-04,138 -NatNgs,MrzDPQFG57w,q4xZArgOIWc,entertaining_relaxing,0,10,2023-09-04,138 -NatNgs,NEVapv8c-SM,q4xZArgOIWc,entertaining_relaxing,5,10,2023-03-13,113 -NatNgs,NEVapv8c-SM,q4xZArgOIWc,importance,7,10,2023-03-13,113 -NatNgs,NEVapv8c-SM,q4xZArgOIWc,largely_recommended,7,10,2023-03-13,113 -NatNgs,fXaz1dM9dq8,q4xZArgOIWc,largely_recommended,8,10,2023-03-13,113 -NatNgs,fXaz1dM9dq8,q4xZArgOIWc,importance,9,10,2023-03-13,113 -NatNgs,fXaz1dM9dq8,q4xZArgOIWc,entertaining_relaxing,8,10,2023-03-13,113 -NatNgs,6mgQwzom0Xo,q4xZArgOIWc,largely_recommended,6,10,2023-03-13,113 -NatNgs,6mgQwzom0Xo,q4xZArgOIWc,entertaining_relaxing,-2,10,2023-03-13,113 -NatNgs,6mgQwzom0Xo,q4xZArgOIWc,importance,10,10,2023-03-13,113 -NatNgs,_X3DngmZDzs,q4xZArgOIWc,largely_recommended,10,10,2023-04-10,117 -NatNgs,_X3DngmZDzs,q4xZArgOIWc,importance,10,10,2023-04-10,117 -NatNgs,_X3DngmZDzs,q4xZArgOIWc,entertaining_relaxing,7,10,2023-04-10,117 -NatNgs,VJ61CF9sxm4,4ZX9T0kWb4Y,entertaining_relaxing,-6,10,2023-04-24,119 -NatNgs,VJ61CF9sxm4,4ZX9T0kWb4Y,largely_recommended,-4,10,2023-04-24,119 -NatNgs,VJ61CF9sxm4,4ZX9T0kWb4Y,importance,0,10,2023-04-24,119 -NatNgs,xbdUlfYCRwc,4ZX9T0kWb4Y,largely_recommended,-9,10,2023-04-24,119 -NatNgs,xbdUlfYCRwc,4ZX9T0kWb4Y,importance,-6,10,2023-04-24,119 -NatNgs,xbdUlfYCRwc,4ZX9T0kWb4Y,entertaining_relaxing,2,10,2023-04-24,119 -NatNgs,EcYcIAaTeRA,PtBkkKviXH8,importance,-10,10,2023-05-22,123 -NatNgs,EcYcIAaTeRA,PtBkkKviXH8,largely_recommended,-5,10,2023-05-22,123 -NatNgs,EcYcIAaTeRA,PtBkkKviXH8,entertaining_relaxing,-7,10,2023-05-22,123 -NatNgs,EcYcIAaTeRA,YcXx4Q2ingo,largely_recommended,-7,10,2023-12-04,151 -NatNgs,EcYcIAaTeRA,YcXx4Q2ingo,entertaining_relaxing,-8,10,2023-12-04,151 -NatNgs,EcYcIAaTeRA,YcXx4Q2ingo,importance,-7,10,2023-12-04,151 -NatNgs,4ZX9T0kWb4Y,U3aXWizDbQ4,largely_recommended,5,10,2023-05-29,124 -NatNgs,4ZX9T0kWb4Y,U3aXWizDbQ4,importance,4,10,2023-05-29,124 -NatNgs,4ZX9T0kWb4Y,U3aXWizDbQ4,entertaining_relaxing,2,10,2023-05-29,124 -NatNgs,4ZX9T0kWb4Y,N4oQfWeSmCg,largely_recommended,-2,10,2023-07-17,131 -NatNgs,4ZX9T0kWb4Y,N4oQfWeSmCg,importance,-2,10,2023-07-17,131 -NatNgs,4ZX9T0kWb4Y,N4oQfWeSmCg,entertaining_relaxing,0,10,2023-07-17,131 -NatNgs,4ZX9T0kWb4Y,pSdJBKhDmNo,largely_recommended,3,10,2023-10-23,145 -NatNgs,4ZX9T0kWb4Y,pSdJBKhDmNo,entertaining_relaxing,3,10,2023-10-23,145 -NatNgs,4ZX9T0kWb4Y,pSdJBKhDmNo,importance,1,10,2023-10-23,145 -NatNgs,q4xZArgOIWc,mhLKT4D2YvI,largely_recommended,1,10,2023-07-03,129 -NatNgs,q4xZArgOIWc,mhLKT4D2YvI,importance,1,10,2023-07-03,129 -NatNgs,q4xZArgOIWc,mhLKT4D2YvI,entertaining_relaxing,-1,10,2023-07-03,129 -NatNgs,q4xZArgOIWc,LsMNe_a5Xn0,largely_recommended,3,10,2023-09-11,139 -NatNgs,q4xZArgOIWc,LsMNe_a5Xn0,importance,4,10,2023-09-11,139 -NatNgs,q4xZArgOIWc,LsMNe_a5Xn0,entertaining_relaxing,-1,10,2023-09-11,139 -NatNgs,q4xZArgOIWc,DSBMM2o-fsE,largely_recommended,-3,10,2023-11-20,149 -NatNgs,q4xZArgOIWc,DSBMM2o-fsE,importance,1,10,2023-11-20,149 -NatNgs,q4xZArgOIWc,DSBMM2o-fsE,entertaining_relaxing,-6,10,2023-11-20,149 -NatNgs,E9c2y0eUBMs,EcYcIAaTeRA,entertaining_relaxing,7,10,2023-09-04,138 -NatNgs,E9c2y0eUBMs,EcYcIAaTeRA,importance,-3,10,2023-09-04,138 -NatNgs,E9c2y0eUBMs,EcYcIAaTeRA,largely_recommended,4,10,2023-09-04,138 -NatNgs,rJZyPdYIbZI,4ZX9T0kWb4Y,largely_recommended,-3,10,2023-09-04,138 -NatNgs,rJZyPdYIbZI,4ZX9T0kWb4Y,importance,3,10,2023-09-04,138 -NatNgs,rJZyPdYIbZI,4ZX9T0kWb4Y,entertaining_relaxing,2,10,2023-09-04,138 -NatNgs,vFO9k15xYBs,4ZX9T0kWb4Y,largely_recommended,-2,10,2023-09-18,140 -NatNgs,vFO9k15xYBs,4ZX9T0kWb4Y,importance,-1,10,2023-09-18,140 -NatNgs,vFO9k15xYBs,4ZX9T0kWb4Y,entertaining_relaxing,-6,10,2023-09-18,140 -NatNgs,B0OuIi2YADc,4ZX9T0kWb4Y,entertaining_relaxing,6,10,2023-09-25,141 -NatNgs,B0OuIi2YADc,4ZX9T0kWb4Y,importance,5,10,2023-09-25,141 -NatNgs,B0OuIi2YADc,4ZX9T0kWb4Y,largely_recommended,3,10,2023-09-25,141 -NatNgs,7dkDxmZPWD4,svVFn1XDboo,largely_recommended,-10,10,2023-10-23,145 -NatNgs,7dkDxmZPWD4,5nW3nJhBHL0,entertaining_relaxing,1,10,2024-02-12,161 -NatNgs,7dkDxmZPWD4,5nW3nJhBHL0,importance,-3,10,2024-02-12,161 -NatNgs,7dkDxmZPWD4,5nW3nJhBHL0,largely_recommended,-3,10,2024-02-12,161 -NatNgs,-shvArQdl8M,n3Xv_g3g-mA,importance,9,10,2023-10-23,145 -NatNgs,-shvArQdl8M,n3Xv_g3g-mA,largely_recommended,10,10,2023-10-23,145 -NatNgs,-shvArQdl8M,n3Xv_g3g-mA,entertaining_relaxing,6,10,2023-10-23,145 -NatNgs,-shvArQdl8M,REni8Oi1QJQ,entertaining_relaxing,6,10,2023-10-23,145 -NatNgs,-shvArQdl8M,REni8Oi1QJQ,importance,10,10,2023-10-23,145 -NatNgs,-shvArQdl8M,REni8Oi1QJQ,largely_recommended,9,10,2023-10-23,145 -NatNgs,-shvArQdl8M,X5FPzsKCKd0,largely_recommended,9,10,2023-10-23,145 -NatNgs,-shvArQdl8M,X5FPzsKCKd0,importance,8,10,2023-10-23,145 -NatNgs,-shvArQdl8M,X5FPzsKCKd0,entertaining_relaxing,9,10,2023-10-23,145 -NatNgs,DqhXsEgLMJ0,X-iSQQgOd1A,largely_recommended,-4,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,X-iSQQgOd1A,importance,-3,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,X-iSQQgOd1A,entertaining_relaxing,-1,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,YcXx4Q2ingo,largely_recommended,6,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,YcXx4Q2ingo,entertaining_relaxing,-3,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,YcXx4Q2ingo,importance,1,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,muPcHs-E4qc,entertaining_relaxing,3,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,muPcHs-E4qc,largely_recommended,5,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,muPcHs-E4qc,importance,9,10,2023-11-06,147 -NatNgs,DqhXsEgLMJ0,RQY6WGOoYis,largely_recommended,5,10,2024-09-30,194 -NatNgs,DqhXsEgLMJ0,RQY6WGOoYis,importance,6,10,2024-09-30,194 -NatNgs,DqhXsEgLMJ0,RQY6WGOoYis,entertaining_relaxing,-1,10,2024-09-30,194 -NatNgs,L5s5_zcmcDE,EcYcIAaTeRA,importance,5,10,2023-11-27,150 -NatNgs,L5s5_zcmcDE,EcYcIAaTeRA,largely_recommended,8,10,2023-11-27,150 -NatNgs,L5s5_zcmcDE,EcYcIAaTeRA,entertaining_relaxing,8,10,2023-11-27,150 -NatNgs,9giBKe1VwKU,EcYcIAaTeRA,largely_recommended,8,10,2024-01-01,155 -NatNgs,9giBKe1VwKU,EcYcIAaTeRA,importance,-1,10,2024-01-01,155 -NatNgs,9giBKe1VwKU,EcYcIAaTeRA,entertaining_relaxing,8,10,2024-01-01,155 -NatNgs,_ElagKA5T44,-shvArQdl8M,largely_recommended,-2,10,2024-02-12,161 -NatNgs,_ElagKA5T44,-shvArQdl8M,importance,-1,10,2024-02-12,161 -NatNgs,_ElagKA5T44,-shvArQdl8M,entertaining_relaxing,1,10,2024-02-12,161 -NatNgs,gsEOELSDZvI,q4xZArgOIWc,largely_recommended,4,10,2024-03-04,164 -NatNgs,gsEOELSDZvI,q4xZArgOIWc,importance,5,10,2024-03-04,164 -NatNgs,gsEOELSDZvI,q4xZArgOIWc,entertaining_relaxing,7,10,2024-03-04,164 -NatNgs,cjMfVe8wScM,rgrTqJ5RDjw,entertaining_relaxing,-2,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,rgrTqJ5RDjw,importance,1,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,rgrTqJ5RDjw,largely_recommended,2,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,bG19b06NG_w,importance,8,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,bG19b06NG_w,largely_recommended,5,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,bG19b06NG_w,entertaining_relaxing,-1,10,2024-10-07,195 -NatNgs,cjMfVe8wScM,_pNRuafoyZ4,largely_recommended,8,10,2024-10-14,196 -NatNgs,cjMfVe8wScM,_pNRuafoyZ4,importance,9,10,2024-10-14,196 -NatNgs,cjMfVe8wScM,_pNRuafoyZ4,entertaining_relaxing,-3,10,2024-10-14,196 -NatNgs,cjMfVe8wScM,RQY6WGOoYis,importance,9,10,2024-10-21,197 -NatNgs,cjMfVe8wScM,RQY6WGOoYis,largely_recommended,5,10,2024-10-21,197 -NatNgs,cjMfVe8wScM,RQY6WGOoYis,entertaining_relaxing,-5,10,2024-10-21,197 -NatNgs,EjJLlhLnliQ,D3bHKdMNxzM,importance,2,10,2024-10-07,195 -NatNgs,EjJLlhLnliQ,D3bHKdMNxzM,largely_recommended,-1,10,2024-10-07,195 -NatNgs,EjJLlhLnliQ,D3bHKdMNxzM,entertaining_relaxing,-4,10,2024-10-07,195 -NatNgs,EjJLlhLnliQ,vTMF6xEiAaY,importance,-2,10,2024-10-07,195 -NatNgs,EjJLlhLnliQ,vTMF6xEiAaY,largely_recommended,-5,10,2024-10-07,195 -NatNgs,EjJLlhLnliQ,vTMF6xEiAaY,entertaining_relaxing,2,10,2024-10-07,195 -NatNgs,5HGwcFoeQ9Y,7dkDxmZPWD4,entertaining_relaxing,4,10,2024-10-07,195 -NatNgs,5HGwcFoeQ9Y,7dkDxmZPWD4,largely_recommended,7,10,2024-10-07,195 -NatNgs,5HGwcFoeQ9Y,7dkDxmZPWD4,importance,3,10,2024-10-07,195 -NatNgs,7Jfz3YBeY9c,cjMfVe8wScM,largely_recommended,-8,10,2024-10-07,195 -NatNgs,7Jfz3YBeY9c,cjMfVe8wScM,entertaining_relaxing,3,10,2024-10-07,195 -NatNgs,7Jfz3YBeY9c,cjMfVe8wScM,importance,-10,10,2024-10-07,195 -NatNgs,YdTErpJZ-_4,-shvArQdl8M,largely_recommended,-2,10,2024-10-14,196 -NatNgs,YdTErpJZ-_4,-shvArQdl8M,entertaining_relaxing,-1,10,2024-10-14,196 -NatNgs,YdTErpJZ-_4,-shvArQdl8M,importance,-1,10,2024-10-14,196 -NatNgs,aHFGvob2oMc,bQF51mqzrY4,importance,1,10,2024-10-21,197 -NatNgs,aHFGvob2oMc,bQF51mqzrY4,largely_recommended,-1,10,2024-10-21,197 -NatNgs,aHFGvob2oMc,bQF51mqzrY4,entertaining_relaxing,3,10,2024-10-21,197 -oscarv,kNF0LkIodXw,K5f71XKwhPE,importance,-2,10,2021-04-05,12 -oscarv,2cSH3mErTnE,C_gMPaP8x5I,largely_recommended,9,10,2023-03-06,112 -oscarv,C_gMPaP8x5I,ahbWtVru4lw,largely_recommended,-5,10,2023-03-06,112 -oscarv,C_gMPaP8x5I,F1Hq8eVOMHs,largely_recommended,-2,10,2023-03-13,113 -oscarv,C_gMPaP8x5I,aESqrP3hfi8,largely_recommended,-4,10,2023-03-13,113 -oscarv,C_gMPaP8x5I,bgIIPT6hZRk,largely_recommended,6,10,2023-12-04,151 -oscarv,C_gMPaP8x5I,cZRedorx7Vk,largely_recommended,-3,10,2024-02-19,162 -oscarv,JcFRbecX6bk,C_gMPaP8x5I,largely_recommended,2,10,2023-03-06,112 -oscarv,P_euKVv7gE8,K5f71XKwhPE,largely_recommended,3,10,2023-06-05,125 -oscarv,5bPshVQMcuY,K5f71XKwhPE,largely_recommended,-10,10,2023-06-05,125 -oscarv,0ZZ8CmI_AHI,K5f71XKwhPE,largely_recommended,-9,10,2023-06-12,126 -oscarv,K5f71XKwhPE,ti10FPTVPcI,largely_recommended,8,10,2023-09-11,139 -oscarv,L8vLG8DAGyU,K5f71XKwhPE,largely_recommended,-7,10,2024-04-01,168 -timber,WomtTTubsSU,EcYcIAaTeRA,largely_recommended,4,10,2022-09-05,86 -timber,WomtTTubsSU,EcYcIAaTeRA,importance,-4,10,2022-09-05,86 -timber,WomtTTubsSU,EcYcIAaTeRA,entertaining_relaxing,3,10,2022-09-05,86 -timber,EcYcIAaTeRA,Euwztpe2JtY,largely_recommended,-3,10,2022-11-21,97 -timber,EcYcIAaTeRA,XdFm3avwKNQ,largely_recommended,-3,10,2022-11-21,97 -timber,EcYcIAaTeRA,aYP7WXhQQFY,largely_recommended,6,10,2022-11-21,97 -timber,EcYcIAaTeRA,IVqXKP91L4E,largely_recommended,6,10,2022-11-21,97 -timber,OzQYXshYM2w,EcYcIAaTeRA,largely_recommended,-3,10,2022-11-21,97 -timber,lYXQvHhfKuM,EcYcIAaTeRA,largely_recommended,-3,10,2022-11-28,98 -timber,vs_Zzf_vL2I,EcYcIAaTeRA,largely_recommended,2,10,2022-11-28,98 -timber,46QRfChKDgg,xaQJbozY_Is,largely_recommended,4,10,2022-11-28,98 -timber,6Pm0Mn0-jYU,EcYcIAaTeRA,largely_recommended,-5,10,2022-11-28,98 -timber,tCbXk5P3Mjc,EcYcIAaTeRA,largely_recommended,-4,10,2023-01-16,105 -timber,gtXHv95pwyE,EcYcIAaTeRA,largely_recommended,-5,10,2023-01-30,107 -timber,_f6HzL0Nh2g,EcYcIAaTeRA,largely_recommended,-4,10,2023-01-30,107 -timber,6gjMfVcKA_o,EcYcIAaTeRA,largely_recommended,-5,10,2023-01-30,107 -timber,5mVza6L3DHU,EcYcIAaTeRA,largely_recommended,-3,10,2023-05-01,120 -Tit0uan,h5WjRjz5mTU,z9oRjAMwt9M,largely_recommended,-9,10,2024-05-13,174 -Tit0uan,IQbHp-r2o1k,z9oRjAMwt9M,largely_recommended,-9,10,2024-05-20,175 -Tit0uan,Jtmo3T98eQw,z9oRjAMwt9M,largely_recommended,-10,10,2024-05-27,176 -Tit0uan,xMxo9pIC0GA,flMOPiwaeQ4,largely_recommended,2,10,2024-09-30,194 -Tit0uan,xMxo9pIC0GA,sGLiSLAlwrY,largely_recommended,7,10,2024-09-30,194 -Tit0uan,xMxo9pIC0GA,mqMUniMScGw,largely_recommended,5,10,2024-09-30,194 -Tit0uan,xMxo9pIC0GA,fS02ZZGnZQA,largely_recommended,3,10,2024-09-30,194 -Tit0uan,w5ebcowAJD8,xMxo9pIC0GA,largely_recommended,4,10,2024-09-30,194 -Tit0uan,ZP7T6WAK3Ow,rV9_F2gsdhk,largely_recommended,-7,10,2024-10-14,196 -Tit0uan,ZP7T6WAK3Ow,COpQoc8gBWo,largely_recommended,-8,10,2024-10-14,196 -Tit0uan,ZP7T6WAK3Ow,gKgH60hFoRU,largely_recommended,-5,10,2024-10-14,196 -Tit0uan,pXNeM0pingU,ZP7T6WAK3Ow,largely_recommended,5,10,2024-10-14,196 -vero,-shvArQdl8M,aq0xi66rfj4,largely_recommended,6,10,2023-05-22,123 -vero,-shvArQdl8M,aq0xi66rfj4,importance,3,10,2023-05-22,123 -vero,-shvArQdl8M,aq0xi66rfj4,entertaining_relaxing,-3,10,2023-05-22,123 -vero,B96mq3mW0sI,-shvArQdl8M,largely_recommended,-7,10,2023-05-22,123 -white,xeMbGBw7j8g,88Cd5H3kmXQ,largely_recommended,4,10,2022-05-02,68 -white,xeMbGBw7j8g,88Cd5H3kmXQ,entertaining_relaxing,-2,10,2022-05-02,68 -white,xeMbGBw7j8g,88Cd5H3kmXQ,importance,6,10,2022-05-02,68 -white,xeMbGBw7j8g,JU4Vbw4rF64,largely_recommended,-4,10,2022-05-02,68 -white,xeMbGBw7j8g,JU4Vbw4rF64,entertaining_relaxing,-3,10,2022-05-02,68 -white,xeMbGBw7j8g,JU4Vbw4rF64,importance,-5,10,2022-05-02,68 -white,xeMbGBw7j8g,Br5U38OheyM,largely_recommended,4,10,2022-05-02,68 -white,xeMbGBw7j8g,Br5U38OheyM,importance,2,10,2022-05-02,68 -white,xeMbGBw7j8g,Br5U38OheyM,entertaining_relaxing,-1,10,2022-05-02,68 -white,xeMbGBw7j8g,-TxzW4eklEU,largely_recommended,-4,10,2022-05-02,68 -white,xeMbGBw7j8g,-TxzW4eklEU,importance,1,10,2022-05-02,68 -white,xeMbGBw7j8g,-TxzW4eklEU,entertaining_relaxing,-1,10,2022-05-02,68 -white,IYrcgjlIDyM,xeMbGBw7j8g,largely_recommended,-4,10,2022-05-02,68 -white,IYrcgjlIDyM,xeMbGBw7j8g,importance,-9,10,2022-05-02,68 -white,IYrcgjlIDyM,xeMbGBw7j8g,entertaining_relaxing,7,10,2022-05-02,68 -white,V-1RhQ1uuQ4,xeMbGBw7j8g,largely_recommended,-1,10,2022-05-16,70 -white,V-1RhQ1uuQ4,xeMbGBw7j8g,importance,-2,10,2022-05-16,70 -white,V-1RhQ1uuQ4,xeMbGBw7j8g,entertaining_relaxing,1,10,2022-05-16,70 -white,AUO_H-OYzfM,xeMbGBw7j8g,largely_recommended,2,10,2022-05-16,70 -white,AUO_H-OYzfM,xeMbGBw7j8g,importance,7,10,2022-05-16,70 -white,AUO_H-OYzfM,xeMbGBw7j8g,entertaining_relaxing,3,10,2022-05-16,70 -white,ztJmUN_3v7g,xeMbGBw7j8g,importance,-7,10,2022-05-23,71 -white,ztJmUN_3v7g,xeMbGBw7j8g,entertaining_relaxing,9,10,2022-05-23,71 -white,ztJmUN_3v7g,xeMbGBw7j8g,largely_recommended,5,10,2022-05-23,71 -white,YVxJNhR9U4g,fkbZ60JXXB8,entertaining_relaxing,6,10,2022-06-06,73 -white,YVxJNhR9U4g,fkbZ60JXXB8,importance,-6,10,2022-06-06,73 -white,YVxJNhR9U4g,fkbZ60JXXB8,largely_recommended,-1,10,2022-06-06,73 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+Antarctus,entertaining_relaxing,segcFv9UcCg,xeMbGBw7j8g,3,10,2024-07-29,185 +Antarctus,entertaining_relaxing,jbdVG7lXehU,u3iJKE3PdEM,2,10,2024-09-30,194 +Antarctus,entertaining_relaxing,u3iJKE3PdEM,5iPH-br_eJQ,7,10,2024-09-30,194 +Antarctus,entertaining_relaxing,u3iJKE3PdEM,N_ayq66t77U,8,10,2024-10-07,195 +Antarctus,entertaining_relaxing,2cvj2-Vh8Uc,E1Dn3F7Ili8,-2,10,2024-10-07,195 +Antarctus,entertaining_relaxing,WazrsWXi44k,u3iJKE3PdEM,-4,10,2024-10-07,195 +Antarctus,entertaining_relaxing,ZP7T6WAK3Ow,eMn43As24Bo,-2,10,2024-10-14,196 +Antarctus,entertaining_relaxing,ZP7T6WAK3Ow,_rBPwu2uS-w,-2,10,2024-10-14,196 +Antarctus,entertaining_relaxing,ZP7T6WAK3Ow,UjtOGPJ0URM,5,10,2024-10-14,196 +Antarctus,entertaining_relaxing,ZP7T6WAK3Ow,j2zv4jlo2Nw,-5,10,2024-10-14,196 +Antarctus,entertaining_relaxing,ZP7T6WAK3Ow,u3iJKE3PdEM,-2,10,2024-10-14,196 +Antarctus,entertaining_relaxing,rJE2qkP0Gk4,xeMbGBw7j8g,-5,10,2024-10-21,197 +Antarctus,importance,xeMbGBw7j8g,auKJTuT3LV4,3,10,2024-07-29,185 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+Antarctus,largely_recommended,jbdVG7lXehU,u3iJKE3PdEM,-4,10,2024-09-30,194 +Antarctus,largely_recommended,u3iJKE3PdEM,5iPH-br_eJQ,6,10,2024-09-30,194 +Antarctus,largely_recommended,u3iJKE3PdEM,N_ayq66t77U,6,10,2024-10-07,195 +Antarctus,largely_recommended,2cvj2-Vh8Uc,E1Dn3F7Ili8,-4,10,2024-10-07,195 +Antarctus,largely_recommended,WazrsWXi44k,u3iJKE3PdEM,-3,10,2024-10-07,195 +Antarctus,largely_recommended,ZP7T6WAK3Ow,eMn43As24Bo,-3,10,2024-10-14,196 +Antarctus,largely_recommended,ZP7T6WAK3Ow,_rBPwu2uS-w,0,10,2024-10-14,196 +Antarctus,largely_recommended,ZP7T6WAK3Ow,UjtOGPJ0URM,0,10,2024-10-14,196 +Antarctus,largely_recommended,ZP7T6WAK3Ow,j2zv4jlo2Nw,1,10,2024-10-14,196 +Antarctus,largely_recommended,ZP7T6WAK3Ow,u3iJKE3PdEM,-5,10,2024-10-14,196 +Antarctus,largely_recommended,rJE2qkP0Gk4,xeMbGBw7j8g,0,10,2024-10-21,197 +biscuissec,largely_recommended,XRk2VeL0icU,FGR9VUcvgY8,1,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,VKsekCHBuHI,1,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,oakWgLqCwUc,1,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,qp5HPksrhNE,-3,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,x3rptRn6GeA,-3,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,2__Dd_KXuuU,1,10,2021-12-06,47 +biscuissec,largely_recommended,XRk2VeL0icU,CG8yN4A4fuM,-4,10,2021-12-06,47 +biscuissec,largely_recommended,PgUN1uy8PYE,XREXROcadQM,2,10,2021-12-13,48 +biscuissec,largely_recommended,OlmXLuz2_mc,fksKuXhvWX4,2,10,2022-02-07,56 +biscuissec,largely_recommended,FhjOz4ofy4g,fksKuXhvWX4,6,10,2022-02-07,56 +biscuissec,largely_recommended,fksKuXhvWX4,DV1x_9z_LMc,-6,10,2022-02-07,56 +biscuissec,largely_recommended,fksKuXhvWX4,vN2hmYyQo3o,-10,10,2022-02-07,56 +biscuissec,largely_recommended,fksKuXhvWX4,SCYMx75Ao8A,-2,10,2022-02-14,57 +biscuissec,largely_recommended,yAtDuXaEtFI,fksKuXhvWX4,0,10,2022-02-14,57 +biscuissec,largely_recommended,VY2yv3zMOsI,ju6hC1YF5TM,0,10,2022-08-01,81 +biscuissec,largely_recommended,y6f3dwxexZM,ju6hC1YF5TM,0,10,2022-08-01,81 +biscuissec,largely_recommended,NxvQPzrg2Wg,ju6hC1YF5TM,0,10,2022-08-01,81 +biscuissec,largely_recommended,SKmgDiDPblA,ju6hC1YF5TM,0,10,2022-08-01,81 +biscuissec,largely_recommended,j7h75zxDEW8,ju6hC1YF5TM,0,10,2022-08-01,81 +biscuissec,largely_recommended,ju6hC1YF5TM,nJkJT1uiFB8,0,10,2022-08-01,81 +biscuissec,largely_recommended,ju6hC1YF5TM,5IpAsztfBBA,0,10,2022-08-01,81 +biscuissec,largely_recommended,ju6hC1YF5TM,oakWgLqCwUc,0,10,2022-08-01,81 +biscuissec,largely_recommended,ja6HqVej_yw,ju6hC1YF5TM,0,10,2022-08-15,83 +biscuissec,largely_recommended,TrMSt1xMRWQ,ju6hC1YF5TM,0,10,2022-08-15,83 +biscuissec,largely_recommended,eNvboEAaMyE,ju6hC1YF5TM,0,10,2022-08-15,83 +biscuissec,largely_recommended,Z6tKCJhlN9U,Vp_GDh1yQ-4,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,OIsPAA9T7m4,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,Po4O-gwvuQY,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,HPdHj7rqLyc,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,trg06GQ3VkU,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,DwqwRYe6fKA,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,yT01CAWDtGM,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,n3Xv_g3g-mA,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,I9hJ_Rux9y0,0,10,2022-09-05,86 +biscuissec,largely_recommended,Z6tKCJhlN9U,HYuqC13LZ1Q,0,10,2022-09-05,86 +biscuissec,largely_recommended,dnT_Fu3CLPw,V6ChTqII-Yk,-3,10,2022-09-12,87 +biscuissec,largely_recommended,baxj1kuaWJ8,V6ChTqII-Yk,-3,10,2022-09-19,88 +biscuissec,largely_recommended,c2VgEeq_V48,V6ChTqII-Yk,-1,10,2022-09-26,89 +biscuissec,largely_recommended,XulBKrrRC3k,V6ChTqII-Yk,0,10,2022-10-03,90 +biscuissec,largely_recommended,rvskMHn0sqQ,BDQX_Whx--E,0,10,2022-10-10,91 +biscuissec,largely_recommended,J5LodnKnLYU,BDQX_Whx--E,0,10,2022-10-10,91 +biscuissec,largely_recommended,2wXjSyoWmeg,BDQX_Whx--E,0,10,2022-10-10,91 +biscuissec,largely_recommended,GNmp_T2OWfk,BDQX_Whx--E,0,10,2022-10-10,91 +biscuissec,largely_recommended,IYblisCkLiw,BDQX_Whx--E,0,10,2022-10-10,91 +biscuissec,largely_recommended,BDQX_Whx--E,KOZXFn3P_AE,0,10,2022-10-10,91 +biscuissec,largely_recommended,BDQX_Whx--E,rFGjqet5o2c,0,10,2022-10-10,91 +biscuissec,largely_recommended,BDQX_Whx--E,ZzH-bAY6KGI,0,10,2022-10-10,91 +biscuissec,largely_recommended,BDQX_Whx--E,nJslrTT-Yhc,-2,10,2022-10-31,94 +biscuissec,largely_recommended,BDQX_Whx--E,MqmSMunAtss,0,10,2022-10-31,94 +biscuissec,largely_recommended,kxV8mkfzYrI,aIp-aa8F9EI,10,10,2022-10-24,93 +biscuissec,largely_recommended,Tt5AwEU_BiM,iOlz5OBMr7A,-7,10,2022-11-07,95 +biscuissec,largely_recommended,Tt5AwEU_BiM,cQcHghE856E,3,10,2022-11-07,95 +biscuissec,largely_recommended,vzJAvChiozY,Tt5AwEU_BiM,4,10,2022-11-14,96 +biscuissec,largely_recommended,dAMXH2_dcvs,Tt5AwEU_BiM,4,10,2022-11-21,97 +biscuissec,largely_recommended,46QRfChKDgg,xaQJbozY_Is,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,hCQ_qvxcf_o,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,YW3rHvMh5AE,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,9gPv4qzzb9Q,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,rd6Z0HQenuM,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,u148ZVqBBgY,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,QT-oDKHn-Fo,0,10,2022-11-28,98 +biscuissec,largely_recommended,46QRfChKDgg,KJ04GQYWH28,-10,10,2023-06-12,126 +biscuissec,largely_recommended,bL_8xKAyP_U,46QRfChKDgg,-3,10,2022-11-28,98 +biscuissec,largely_recommended,aIp-aa8F9EI,PkYXSCXMg_8,-10,10,2022-12-12,100 +biscuissec,largely_recommended,JXeJANDKwDc,uljTEmmCh_E,0,10,2023-01-23,106 +biscuissec,largely_recommended,d35JQvaEen0,uljTEmmCh_E,0,10,2023-01-23,106 +biscuissec,largely_recommended,9BBqFZwBsgs,uljTEmmCh_E,0,10,2023-01-23,106 +biscuissec,largely_recommended,bAn5zcG8-HA,uljTEmmCh_E,0,10,2023-01-23,106 +biscuissec,largely_recommended,igtR3tsRkqk,uljTEmmCh_E,0,10,2023-01-23,106 +biscuissec,largely_recommended,uljTEmmCh_E,7WGaMAb-ivs,0,10,2023-01-23,106 +biscuissec,largely_recommended,uljTEmmCh_E,K9UE2WD6nu8,0,10,2023-01-23,106 +biscuissec,largely_recommended,uljTEmmCh_E,ZoSlPBuZtO4,0,10,2023-02-13,109 +biscuissec,largely_recommended,uljTEmmCh_E,6gjMfVcKA_o,0,10,2023-02-13,109 +biscuissec,largely_recommended,uljTEmmCh_E,uYYRAPBbr_w,0,10,2023-02-20,110 +biscuissec,largely_recommended,uljTEmmCh_E,SgxGQ7-3u-I,-10,10,2023-02-27,111 +biscuissec,largely_recommended,tRhfOtpYG2U,C_gMPaP8x5I,1,10,2023-03-06,112 +biscuissec,largely_recommended,3DOcQRl9ASc,C_gMPaP8x5I,0,10,2023-03-06,112 +biscuissec,largely_recommended,JAdhaZqU_Fw,C_gMPaP8x5I,3,10,2023-03-06,112 +biscuissec,largely_recommended,C_gMPaP8x5I,V6x9bXTU0vY,-1,10,2023-03-06,112 +biscuissec,largely_recommended,xeMbGBw7j8g,8y67NFHpxwI,-1,10,2023-03-20,114 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