{"id":"W2932847212","doi":"10.1016/j.envint.2019.03.042","title":"Evaluating the potential public health impacts of the Toronto cold weather program","year":2019,"lang":"en","type":"article","venue":"Environment International","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto; Public Health Ontario","funders":"","keywords":"Extreme Cold; Cold weather; Propensity score matching; Environmental health; Medicine; Public health; Coronary heart disease; Extreme weather; Demography; Geography; Meteorology; Climatology; Climate change; Internal medicine","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":[0.01473016,0.0004023569,0.0003202962,0.0004574685,0.0006137421,0.0008138476,0.0008373453,0.0005012209,0.002498453],"category_scores_gemma":[0.02199844,0.0001687261,0.0009664918,0.0008055496,0.000898143,0.0004387491,0.0008975784,0.0005771423,0.00008556156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01123768,"about_ca_system_score_gemma":0.01843873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3306184,"about_ca_topic_score_gemma":0.3274776,"domain_scores_codex":[0.9879788,0.009295347,0.0002591667,0.0003518247,0.001406195,0.000708574],"domain_scores_gemma":[0.9822776,0.0106756,0.003614308,0.0005985363,0.001583689,0.001250267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02331407,0.007000087,0.7661988,0.004321599,0.006123209,0.0002976267,0.001611268,0.06354821,0.002445296,0.00584262,0.004124651,0.1151727],"study_design_scores_gemma":[0.002131604,0.02220214,0.9526802,0.0003090606,0.002645227,0.00004620675,0.00108458,0.0127169,0.001910211,0.0008423647,0.003384433,0.00004706349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858401,0.001013126,0.002136763,0.00155278,0.00005231005,0.001875659,0.00205653,0.00002356153,0.00544921],"genre_scores_gemma":[0.9971654,0.0002765311,0.001297679,0.0001421932,0.0000174714,0.0004215357,0.0003588376,0.000001786141,0.0003185835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6693816,"threshold_uncertainty_score":0.657388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07485701061158516,"score_gpt":0.3702796581166032,"score_spread":0.2954226475050181,"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."}}