{"id":"W2095887717","doi":"10.1093/biostatistics/3.2.229","title":"A Bayesian approach to case-control studies with errors in covariables","year":2002,"lang":"en","type":"article","venue":"Biostatistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bayesian probability; Computer science; Control (management); Econometrics; Statistics; Artificial intelligence; Mathematics","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":[0.07404706,0.001942058,0.003944329,0.007266919,0.001506846,0.003639593,0.006572803,0.00364299,0.003962041],"category_scores_gemma":[0.1872464,0.001756932,0.002911247,0.006381832,0.004064777,0.003350382,0.003909808,0.006914921,0.000808074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002664373,"about_ca_system_score_gemma":0.005000323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004861398,"about_ca_topic_score_gemma":0.004660575,"domain_scores_codex":[0.9294521,0.05613293,0.003122569,0.003488102,0.007259633,0.0005446374],"domain_scores_gemma":[0.882722,0.1034629,0.004541818,0.005602912,0.002928755,0.0007417179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006496746,0.0001077042,0.002099948,0.0005647328,0.0007374269,0.0004378902,0.0006012455,0.04144092,0.0004952375,0.8673378,0.003496136,0.08261585],"study_design_scores_gemma":[0.00009434753,0.0000863095,0.0004730818,0.0001691288,0.0001649165,0.0002988284,0.0000372884,0.05430382,0.0001653291,0.9364691,0.007692927,0.00004490828],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003543695,0.0007951961,0.9975979,0.0006528398,0.00005823899,0.0001073719,0.00004934719,0.00003275693,0.0003519689],"genre_scores_gemma":[0.03016776,0.003315682,0.9613918,0.0009058045,0.0005538661,0.002454743,0.0002039527,0.00005189614,0.0009544241],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07404706,"threshold_uncertainty_score":0.3916029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1371729806175621,"score_gpt":0.361720640302282,"score_spread":0.2245476596847199,"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."}}