{"id":"W4251178317","doi":"10.31235/osf.io/nrjd3","title":"Sociodemographic Determinants of Occupational Risks of Exposure to COVID-19 in Canada","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Immigration; Environmental health; Demographic economics; Occupational safety and health; Occupational exposure; Work (physics); Medicine; Gerontology; Demography; Geography; Sociology; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00104164,0.0003734553,0.0004287335,0.002110087,0.003489776,0.001778474,0.001147011,0.0003915347,0.005636769],"category_scores_gemma":[0.003526956,0.0003496585,0.0008065366,0.004591629,0.0007292986,0.0004034673,0.001406591,0.0008779906,0.0004284034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03021175,"about_ca_system_score_gemma":0.06168865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.998342,"about_ca_topic_score_gemma":0.9989215,"domain_scores_codex":[0.9985456,0.0001027095,0.00008981147,0.0002057062,0.0004773783,0.0005788982],"domain_scores_gemma":[0.9968994,0.0002248176,0.0005217809,0.0001226307,0.001252776,0.0009785123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001025891,0.00003807031,0.9816324,0.00007207297,0.00009466273,0.0001011838,0.001515396,0.0003924874,0.0001446716,0.0008657402,0.005793453,0.009247377],"study_design_scores_gemma":[0.000008928523,0.00001423551,0.9927208,0.0001160451,0.00003295292,0.00004233467,0.002471873,0.0004419916,0.00006686717,0.0001253519,0.003935812,0.00002269513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454748,0.003081977,0.0005412351,0.002627054,0.00006930631,0.00009921443,0.03371943,0.00004272938,0.01434414],"genre_scores_gemma":[0.9887927,0.001398221,0.0004232632,0.000168327,0.000010412,0.00002474748,0.00528445,0.00001552316,0.003882352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03021175,"threshold_uncertainty_score":0.2192026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3030226904995248,"score_gpt":0.5072382965651921,"score_spread":0.2042156060656674,"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."}}