{"id":"W6977030254","doi":"10.60692/d4rhk-41930","title":"The Blursday Database: Individuals' Temporalities in Covid Times","year":2021,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Adsorption and Cooling Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Université Laval","funders":"","keywords":"Temporalities; Personality; Coronavirus disease 2019 (COVID-19); Pandemic; Time perception; Duration (music); Perception; Isolation (microbiology)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001148978,0.0004356754,0.0006332171,0.004244901,0.0003488797,0.001322431,0.0006400634,0.0006945063,0.01029062],"category_scores_gemma":[0.01431107,0.0002454429,0.0003728011,0.005726119,0.0001510428,0.001106283,0.001186621,0.0003719431,0.004315167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004202292,"about_ca_system_score_gemma":0.0005519828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01200372,"about_ca_topic_score_gemma":0.01086903,"domain_scores_codex":[0.9991201,0.0001624527,0.0002448587,0.0001997985,0.0002088371,0.0000639835],"domain_scores_gemma":[0.9925506,0.002735147,0.001231497,0.001831586,0.001222163,0.0004290315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.004103411,0.0003303568,0.2906485,0.003668623,0.0006026154,0.0005488482,0.003887374,0.006181347,0.004585477,0.006574493,0.4488564,0.2300124],"study_design_scores_gemma":[0.0002657105,0.0003590656,0.5718071,0.0004461195,0.0001775457,0.0006351233,0.002482558,0.01122759,0.003051281,0.004243287,0.4050981,0.0002065639],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1029209,0.001010381,0.004462731,0.0002570496,0.00009485528,0.0002151026,0.8831786,0.002873011,0.004987301],"genre_scores_gemma":[0.2273258,0.0005320006,0.009512053,0.00008162841,0.00008692813,0.0009368634,0.7592884,0.0002654046,0.001970961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01200372,"threshold_uncertainty_score":0.03442556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0243298190282179,"score_gpt":0.206784318169552,"score_spread":0.182454499141334,"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."}}