{"id":"W2136972950","doi":"10.1002/sim.4453","title":"Hierarchical priors for bias parameters in Bayesian sensitivity analysis for unmeasured confounding","year":2012,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of British Columbia; Simon Fraser University","funders":"","keywords":"Prior probability; Covariate; Bayesian probability; Econometrics; Confounding; Computer science; Statistics; 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":[0.122764,0.001968331,0.003035279,0.004307054,0.001454134,0.003431468,0.003828986,0.004168617,0.004457063],"category_scores_gemma":[0.3234968,0.001972278,0.003915062,0.003441975,0.005012622,0.005354222,0.004734823,0.007831172,0.0004745409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003521706,"about_ca_system_score_gemma":0.003131116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004327987,"about_ca_topic_score_gemma":0.003623634,"domain_scores_codex":[0.9143879,0.0756698,0.002025643,0.003302673,0.003940295,0.0006736633],"domain_scores_gemma":[0.6738259,0.3031369,0.006604274,0.01290873,0.003013682,0.0005104854],"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":[0.0002713239,0.00007632637,0.003766597,0.0009528971,0.001111052,0.0003393453,0.0007983941,0.2586491,0.0009130624,0.6470044,0.002477358,0.08364014],"study_design_scores_gemma":[0.0001325626,0.00006126328,0.0008642519,0.0003147224,0.0002608371,0.0001125684,0.00005463558,0.22887,0.0006555423,0.7660044,0.002594733,0.00007439969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002432843,0.0004823196,0.9956163,0.0004527436,0.00003041657,0.0001235583,0.00008140525,0.0001194054,0.0006608916],"genre_scores_gemma":[0.2201408,0.001362805,0.7745187,0.0007578576,0.000208356,0.001461949,0.0002844443,0.0002327376,0.001032268],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.122764,"threshold_uncertainty_score":0.6492457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1546876846126924,"score_gpt":0.4413987125723917,"score_spread":0.2867110279596992,"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."}}