{"id":"W4212770141","doi":"10.14745/ccdr.v48i01a05f","title":"Inégalités sociales des décès liés à la COVID-19 au Canada, par caractéristiques individuelles et locales, de janvier à juillet/août 2020 : résultats de deux processus nationaux d’intégration de données","year":2022,"lang":"fr","type":"article","venue":"Relevé des maladies transmissibles au Canada","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Public Health Agency of Canada","funders":"","keywords":"Political science; Humanities; Coronavirus disease 2019 (COVID-19); Art; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.006787164,0.0006820003,0.001037247,0.003943001,0.003769394,0.003442302,0.002116749,0.0007051532,0.002651407],"category_scores_gemma":[0.0238312,0.0005444564,0.001847581,0.009445877,0.001577361,0.001021201,0.003570368,0.001498734,0.0003303649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04085065,"about_ca_system_score_gemma":0.06900364,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946964,"about_ca_topic_score_gemma":0.9953238,"domain_scores_codex":[0.9939772,0.001314815,0.0005664064,0.00081992,0.002193733,0.0011279],"domain_scores_gemma":[0.9791374,0.003325194,0.003052379,0.0008848404,0.01231177,0.001288363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002219177,0.00007086931,0.9588099,0.0006055773,0.0005298771,0.0001077702,0.01771781,0.0005185432,0.0001745111,0.0005163598,0.004200783,0.01652608],"study_design_scores_gemma":[0.00001335166,0.00004423965,0.9807885,0.0004443506,0.000180566,0.00003352997,0.01109951,0.0003951763,0.0001629178,0.0001036624,0.006691566,0.00004262892],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309685,0.003999359,0.001806519,0.001932376,0.0001036841,0.0009416239,0.0531742,0.00007226077,0.007001483],"genre_scores_gemma":[0.9580508,0.00346224,0.005239649,0.0006866428,0.00003319139,0.001638333,0.02353707,0.00004833022,0.007303679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04085065,"threshold_uncertainty_score":0.2963936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0815705793602863,"score_gpt":0.3449723517178768,"score_spread":0.2634017723575905,"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."}}