{"id":"W4220911108","doi":"10.1016/j.patter.2022.100482","title":"Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic","year":2022,"lang":"en","type":"article","venue":"Patterns","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"European Regional Development Fund; York University; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; New York University Abu Dhabi; Rijksuniversiteit Groningen; Instituto de Salud Carlos III","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Set (abstract data type); Variance (accounting); Psychology; Health behavior; Medicine; Clinical psychology; Disease; Environmental health; Computer science; Infectious disease (medical specialty); Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006956646,0.00009352789,0.0001363426,0.0001088501,0.0003618678,0.000006459095,0.0001709494,0.00003274493,0.0008180319],"category_scores_gemma":[0.00004078761,0.00007015878,0.0001154733,0.0002549143,0.00002925557,0.00004009017,0.0001956151,0.0003035071,0.000001646163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004077619,"about_ca_system_score_gemma":0.0001231686,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02783748,"about_ca_topic_score_gemma":0.00196749,"domain_scores_codex":[0.9984692,0.0004479033,0.0004211206,0.0002004837,0.0002722251,0.0001890483],"domain_scores_gemma":[0.999195,0.0000636141,0.0003786009,0.0002695173,0.00001555134,0.00007767048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001119184,0.000225344,0.9618629,0.00009817253,0.00002636777,0.000002982358,0.008617835,0.0004094144,0.02819355,0.00000736083,0.000006865543,0.000437352],"study_design_scores_gemma":[0.001047615,0.0003669227,0.9956422,0.00002780253,0.00007421929,0.0000284135,0.001020135,0.00008360517,0.001005305,0.00001808674,0.000615479,0.00007021966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975398,0.00006668623,0.0006298323,0.00008431183,0.0008860216,0.0006179933,0.000132554,0.00003187861,0.00001097012],"genre_scores_gemma":[0.9994015,0.0000123419,0.00000262452,0.0001423139,0.00004218689,0.0000762677,0.00001544732,0.00001699047,0.0002902884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03377936,"threshold_uncertainty_score":0.9786363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1034398364558139,"score_gpt":0.4707246715588748,"score_spread":0.3672848351030609,"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."}}