{"id":"W2160044639","doi":"10.1111/j.1365-2753.2008.01053.x","title":"Are (the log‐odds of) hospital mortality rates normally distributed? Implications for studying variations in outcomes of medical care","year":2009,"lang":"en","type":"article","venue":"Journal of Evaluation in Clinical Practice","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Odds; Medicine; Odds ratio; Mortality rate; Health care; Demography; Emergency medicine; Logistic regression; Internal medicine; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2120728,0.001035538,0.002789881,0.003795383,0.0009421172,0.004608551,0.00452235,0.004554559,0.003085829],"category_scores_gemma":[0.7248479,0.0009189213,0.003538677,0.004770622,0.01549075,0.007861994,0.00260601,0.00464571,0.000339114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005002517,"about_ca_system_score_gemma":0.003833641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02108334,"about_ca_topic_score_gemma":0.006297491,"domain_scores_codex":[0.7921283,0.1578407,0.008493166,0.01996717,0.01944358,0.002127031],"domain_scores_gemma":[0.1643946,0.762131,0.04453741,0.02222225,0.005462572,0.001252208],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001577477,0.0002258477,0.7884632,0.001118757,0.005938064,0.0009195304,0.004583933,0.02116192,0.0003374309,0.05911931,0.002338614,0.114216],"study_design_scores_gemma":[0.0004361939,0.001416906,0.6113672,0.001927048,0.001958325,0.001905428,0.003801289,0.1144542,0.0008009693,0.2576364,0.004010476,0.0002855752],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6753866,0.01712629,0.2567109,0.03219715,0.0006087905,0.001042728,0.002223118,0.0004385163,0.01426603],"genre_scores_gemma":[0.984129,0.0006778939,0.01316634,0.001131013,0.0001734956,0.0002714581,0.0002248087,0.00002946628,0.0001965518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7879272,"threshold_uncertainty_score":0.9716545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4096959235620088,"score_gpt":0.6266666729180642,"score_spread":0.2169707493560554,"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."}}