{"id":"W4386608772","doi":"10.2139/ssrn.4511972","title":"Novel Study of Excess Elderly Deaths in Ontario: Updated to 2022","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Excess mortality; Gerontology; Demography; Medicine; Environmental health; Sociology; Population","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":[0.001394764,0.00057929,0.0006728253,0.003904324,0.001287671,0.001762662,0.001131381,0.0007379164,0.004602277],"category_scores_gemma":[0.007357476,0.0005229331,0.001286089,0.01086441,0.0002243188,0.0007686287,0.00125032,0.0006800133,0.0009008058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.012256,"about_ca_system_score_gemma":0.03833975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9683253,"about_ca_topic_score_gemma":0.9867283,"domain_scores_codex":[0.9985403,0.0001012145,0.0002830021,0.0001492712,0.0006906973,0.0002356177],"domain_scores_gemma":[0.9925832,0.0003217843,0.001376304,0.000377907,0.004554724,0.0007861175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007397992,0.00006393877,0.7923876,0.002113415,0.001355784,0.0003914667,0.0009971838,0.0002290983,0.0003560879,0.0003264737,0.1715067,0.02953236],"study_design_scores_gemma":[0.00005265744,0.00001619189,0.9712669,0.0002378761,0.0002634397,0.00007262868,0.0003363908,0.00006676317,0.00005183113,0.00003092258,0.02758574,0.00001865954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2259235,0.02325791,0.0005066399,0.006082416,0.001120859,0.0003356998,0.7185423,0.0001577247,0.02407291],"genre_scores_gemma":[0.7068505,0.01907966,0.002270996,0.005437585,0.001417946,0.0008623799,0.2354783,0.0001449785,0.02845766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03167468,"threshold_uncertainty_score":0.08892387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02489897387071545,"score_gpt":0.2984326397379599,"score_spread":0.2735336658672444,"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."}}