{"id":"W2031038069","doi":"10.1038/jes.2012.22","title":"A Bayesian mixture modeling approach for assessing the effects of correlated exposures in case-control studies","year":2012,"lang":"en","type":"article","venue":"Journal of Exposure Science & Environmental Epidemiology","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Statistics; Logistic regression; Bayesian probability; Econometrics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06600855,0.002819028,0.005613216,0.007626377,0.001623125,0.003723415,0.008444345,0.004804953,0.003670791],"category_scores_gemma":[0.1537182,0.003023377,0.006879358,0.005760512,0.002793012,0.003784094,0.004175745,0.004606208,0.0005608692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001701641,"about_ca_system_score_gemma":0.003131336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01068368,"about_ca_topic_score_gemma":0.006920862,"domain_scores_codex":[0.9537101,0.03718589,0.00184136,0.003658206,0.003065025,0.0005394366],"domain_scores_gemma":[0.8457655,0.1437678,0.003354392,0.004692208,0.001804772,0.0006154403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00125134,0.000490136,0.01834865,0.0011056,0.007991769,0.001026872,0.001157338,0.3726002,0.002306347,0.3321779,0.003335413,0.2582084],"study_design_scores_gemma":[0.0003734588,0.0002995351,0.003209724,0.0002440763,0.001902296,0.0006357749,0.00008241991,0.6937701,0.0004811554,0.2960201,0.002837031,0.0001442938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004201358,0.0009861325,0.9939657,0.0002257646,0.00003730756,0.0000992607,0.0001076314,0.000155843,0.000221074],"genre_scores_gemma":[0.154745,0.002394395,0.838163,0.0003907567,0.0003394831,0.001417144,0.0007295142,0.0001491977,0.001671525],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06600855,"threshold_uncertainty_score":0.3490908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08603609547104074,"score_gpt":0.4115833018628419,"score_spread":0.3255472063918011,"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."}}