{"id":"W4225725556","doi":"10.1097/ede.0000000000001489","title":"Marginal Versus Conditional Odds Ratios When Updating Risk Prediction Models","year":2022,"lang":"en","type":"article","venue":"Epidemiology","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Advancing Health Outcomes; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Odds ratio; Odds; Logistic regression; Diagnostic odds ratio; Population; Variance (accounting); Conditional logistic regression; Confidence interval","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0494009,0.001444159,0.002002044,0.002322138,0.000711191,0.003972596,0.004751836,0.002310633,0.004547342],"category_scores_gemma":[0.3353352,0.001133628,0.001630906,0.001998403,0.002599694,0.006302199,0.004018104,0.005997623,0.001043989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208589,"about_ca_system_score_gemma":0.001508149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003457892,"about_ca_topic_score_gemma":0.00299338,"domain_scores_codex":[0.9615316,0.02754034,0.002263699,0.004026564,0.004043871,0.0005938012],"domain_scores_gemma":[0.810064,0.1565862,0.005816179,0.02229503,0.004512032,0.0007266294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001009976,0.0001744998,0.03321027,0.0008654766,0.0009616374,0.0009553111,0.001266116,0.1626495,0.001836985,0.2477917,0.01028718,0.5389914],"study_design_scores_gemma":[0.0001121762,0.0001798582,0.004673008,0.0002627241,0.0002792056,0.0008682421,0.0001539623,0.601464,0.00354657,0.3758329,0.01248822,0.0001391462],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0109858,0.001005649,0.9842743,0.000799257,0.0002686306,0.00009629288,0.0002098982,0.000948321,0.001411786],"genre_scores_gemma":[0.2868682,0.001147615,0.7073496,0.0006082531,0.000526707,0.0004949042,0.0005253397,0.0007422686,0.001737183],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0494009,"threshold_uncertainty_score":0.26126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2834231463476436,"score_gpt":0.4229138541233788,"score_spread":0.1394907077757352,"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."}}