{"id":"W4291624537","doi":"10.1038/s41562-022-01419-2","title":"The Blursday database as a resource to study subjective temporalities during COVID-19","year":2022,"lang":"en","type":"article","venue":"Nature Human Behaviour","topic":"Psychological and Temporal Perspectives Research","field":"Psychology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; University of Tokyo; Università degli Studi di Padova; Ministero dell’Istruzione, dell’Università e della Ricerca; H2020 European Research Council; Japan Society for the Promotion of Science; Agence Nationale de la Recherche; Dipartimenti di Eccellenza","keywords":"Time perception; Psychology; Perception; Temporalities; Duration (music); Cognitive psychology; Coronavirus disease 2019 (COVID-19); Big Five personality traits; Isolation (microbiology); Pandemic; Personality; Database; Applied psychology; Computer science; Social psychology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001665645,0.0004973213,0.0009748427,0.003234991,0.000408003,0.001186816,0.001008052,0.0007229979,0.01969788],"category_scores_gemma":[0.01001743,0.0003973157,0.0005388989,0.003589458,0.0001727711,0.00103805,0.001872081,0.0005637836,0.009629767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005101811,"about_ca_system_score_gemma":0.0008742156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009867674,"about_ca_topic_score_gemma":0.01765027,"domain_scores_codex":[0.999061,0.0002142875,0.0002138994,0.0001388656,0.0002952504,0.00007670124],"domain_scores_gemma":[0.9912909,0.002925132,0.00115497,0.001775008,0.002116449,0.0007375301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004037674,0.0003841307,0.0437892,0.005252149,0.000338112,0.0003630756,0.002160612,0.001406168,0.004243873,0.002741219,0.7587796,0.1765042],"study_design_scores_gemma":[0.0004267496,0.0003948903,0.2215288,0.000771281,0.000183005,0.0003726871,0.00119856,0.002062979,0.003548628,0.002927496,0.7663643,0.0002206311],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03477746,0.001554072,0.005444999,0.0002531414,0.0001430466,0.0005916912,0.943756,0.004645442,0.008834195],"genre_scores_gemma":[0.06113382,0.0008975786,0.01499512,0.0001997009,0.0001351837,0.002938652,0.9123672,0.001106804,0.006225946],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01969788,"threshold_uncertainty_score":0.06589597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06942963665215092,"score_gpt":0.4465649041574005,"score_spread":0.3771352675052496,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}