{"id":"W2054292793","doi":"10.1097/00042752-200603000-00004","title":"Understanding the Relationship Between Risks and Odds Ratios","year":2006,"lang":"en","type":"article","venue":"Clinical Journal of Sport Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"","keywords":"Relative risk; Odds ratio; Medicine; Confidence interval; Confounding; Statistics; Logistic regression; Odds; Zhàng; Mathematics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004914806,0.00009205959,0.0004801928,0.00005689155,0.0001089063,0.00001398148,0.0001321097,0.00009440076,0.0000729247],"category_scores_gemma":[0.006145256,0.00004714159,0.00006982117,0.0001309942,0.0005081527,0.00005656204,0.00002025797,0.0005899226,0.000001493107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002607331,"about_ca_system_score_gemma":0.00004907946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009017891,"about_ca_topic_score_gemma":0.000003199169,"domain_scores_codex":[0.9979935,0.00008943638,0.001370255,0.00009643891,0.0003274562,0.0001229053],"domain_scores_gemma":[0.9863614,0.0125805,0.0006913728,0.0001390281,0.0001034877,0.0001241397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001543513,0.00001603148,0.5816905,0.00001193335,0.00001306584,0.00002114164,0.00003281859,9.150117e-8,7.148539e-7,0.4144332,0.002418987,0.001346121],"study_design_scores_gemma":[0.0004137003,0.0001558581,0.4689477,0.0001388215,0.0001228249,0.00003030634,0.0001192014,0.00001203929,7.462585e-7,0.5298454,0.0001823912,0.00003108479],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1565211,0.0001431611,0.8365395,0.004784473,0.0002594301,0.00008502444,0.000001630379,0.000007479517,0.001658246],"genre_scores_gemma":[0.9417819,0.00003563753,0.05635408,0.0001731955,0.00158659,4.534816e-7,9.206642e-7,0.000008465088,0.0000587588],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7852609,"threshold_uncertainty_score":0.7356889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6649133274792299,"score_gpt":0.5362153587461209,"score_spread":0.128697968733109,"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."}}