{"id":"W2169111089","doi":"10.1002/sim.3694","title":"Bayesian analysis of a matched case–control study with expert prior information on both the misclassification of exposure and the exposure–disease association","year":2009,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research","keywords":"Dirichlet distribution; Multinomial distribution; Bayesian probability; Statistics; Association (psychology); Prior probability; Disease; Computer science; A priori and a posteriori; Econometrics; Medicine; Mathematics; Internal medicine; Psychology","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":[0.001295905,0.0001247221,0.0004119241,0.0001633418,0.0001098707,0.00001613575,0.0001051817,0.00003835481,0.00007037725],"category_scores_gemma":[0.003681311,0.00006638584,0.00002782266,0.0006623068,0.0001915176,0.00005876842,0.000006504462,0.0001272402,6.414718e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007093434,"about_ca_system_score_gemma":0.00004162446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006544849,"about_ca_topic_score_gemma":0.0001027573,"domain_scores_codex":[0.9981884,0.0002848055,0.0007549025,0.0001271865,0.0005312153,0.0001134295],"domain_scores_gemma":[0.9954765,0.003166825,0.0006478634,0.000351612,0.0002973141,0.00005982631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009085812,0.0006159298,0.008433769,0.00006518224,0.0005052937,0.00001144453,0.01190925,0.0005046179,0.0000246798,0.96341,0.001399687,0.01221158],"study_design_scores_gemma":[0.008303103,0.0008387669,0.8328381,0.00009079941,0.002718779,0.000004988463,0.009845358,0.09612264,0.00001031903,0.04903958,0.00003303,0.0001545761],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04482671,0.00004269389,0.9480812,0.004429178,0.0000202303,0.001399693,0.0009066858,0.00001806172,0.0002755536],"genre_scores_gemma":[0.9950667,0.0000152023,0.004343916,0.0003399825,0.00001540797,0.0001001968,0.00009313178,0.000004613958,0.00002082715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.95024,"threshold_uncertainty_score":0.4407139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02053217632805361,"score_gpt":0.3356158084710708,"score_spread":0.3150836321430172,"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."}}