{"id":"W2913588687","doi":"10.1002/pds.4701","title":"Conditional validation sampling for consistent risk estimation with binary outcome data subject to misclassification","year":2019,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Reliability and Agreement in Measurement","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Carleton University; Institute of Population and Public Health; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Statistics; Contingency table; Categorical variable; Sampling (signal processing); Sample size determination; Simple random sample; Stratified sampling; Sampling design; Estimator; Odds ratio; Econometrics; Computer science; Medicine; Mathematics; Population","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02353846,0.0001715143,0.0004082971,0.0001372423,0.0003484323,0.00004897667,0.0004756416,0.00006642509,0.0002703247],"category_scores_gemma":[0.007785028,0.0001171512,0.00006072265,0.0002138917,0.0001103149,0.0004178604,0.0001458145,0.0001720535,0.0001795554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005991686,"about_ca_system_score_gemma":0.00006321951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003308892,"about_ca_topic_score_gemma":0.00001407928,"domain_scores_codex":[0.9961367,0.001225331,0.001030431,0.0008736028,0.0004796415,0.0002542844],"domain_scores_gemma":[0.9866155,0.01172826,0.0005127792,0.0007030432,0.000304214,0.0001362503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001259665,0.000128957,0.8813739,0.00005460149,0.0000914702,3.654473e-7,0.0002118966,0.07008699,0.001783871,0.003507182,0.01490348,0.02659758],"study_design_scores_gemma":[0.002473515,0.0002345204,0.5709619,0.00004396816,0.0001855814,0.000008671124,0.0004395479,0.3343747,0.0005228182,0.02656391,0.06378341,0.0004074539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4720392,0.0001107076,0.5101651,0.01495181,0.0004632388,0.001390565,0.0006010855,0.00003770279,0.0002406391],"genre_scores_gemma":[0.9607617,0.00005539811,0.0364016,0.001533962,0.000078697,0.0000720093,0.0008592838,0.000007985687,0.00022933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4887226,"threshold_uncertainty_score":0.9319968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3722356889622388,"score_gpt":0.482635052189559,"score_spread":0.1103993632273202,"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."}}