{"id":"W2735420328","doi":"10.25336/p64c7p","title":"The moderating effect of sociodemographic factors on the predictive power of self-rated health for mortality in Canada","year":2017,"lang":"fr","type":"article","venue":"Canadian Studies in Population","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Demography; Logistic regression; Predictive power; Population; Power (physics); Humanities; Welfare economics; Medicine; Sociology; Economics; Philosophy; Physics","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":[0.003279501,0.0005294242,0.0006187885,0.0007817291,0.001319935,0.001233702,0.0009907953,0.0003113633,0.001914348],"category_scores_gemma":[0.0153483,0.0003311558,0.001301856,0.001577453,0.0007579312,0.0004254894,0.001164536,0.0009145649,0.000161695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0123309,"about_ca_system_score_gemma":0.03181471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9917505,"about_ca_topic_score_gemma":0.9918495,"domain_scores_codex":[0.9986247,0.0004060081,0.00008813427,0.0002409391,0.0003346596,0.0003056324],"domain_scores_gemma":[0.993394,0.002851889,0.0007944313,0.0003780411,0.002054156,0.0005275923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001915083,0.00002006666,0.9863254,0.00005347696,0.000239977,0.00005391474,0.000515783,0.001626148,0.0001091779,0.0002366392,0.0007171848,0.00991068],"study_design_scores_gemma":[0.00001786697,0.0000281595,0.990489,0.00007216887,0.0002555753,0.00003110903,0.0005211126,0.007135754,0.0001680898,0.0001622096,0.001099012,0.00002001467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907042,0.00144104,0.001145837,0.001201419,0.00002778465,0.00003820255,0.003517407,0.00005692293,0.001867128],"genre_scores_gemma":[0.9964599,0.0005286687,0.0007098631,0.00008898046,0.000006527775,0.00001731282,0.00122418,0.00001083757,0.000953636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0123309,"threshold_uncertainty_score":0.08946729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07623197688212599,"score_gpt":0.3921316480544851,"score_spread":0.3158996711723591,"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."}}