{"id":"W7083624843","doi":"10.1007/978-3-032-06593-3_20","title":"Empirical Bayesian Methods and BNNs for Medical OOD Detection","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Geotechnical and construction materials studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Prior probability; Bayes' theorem; Bayesian probability; Bayesian inference; Inference; Artificial neural network; Uncertainty quantification; Empirical probability; Entropy (arrow of time); Predictive inference","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004528135,0.0002175188,0.0003232258,0.0002214379,0.0001229435,0.00007011332,0.0002537514,0.0003137166,0.0000247287],"category_scores_gemma":[0.0001683069,0.000186706,0.00005481602,0.0001277009,0.0003689996,0.00004692114,0.0002104048,0.0003196164,0.000001170307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006175442,"about_ca_system_score_gemma":0.00006516035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002982232,"about_ca_topic_score_gemma":0.00005250001,"domain_scores_codex":[0.9988531,0.00001429688,0.0002640236,0.0004142956,0.0002224265,0.000231842],"domain_scores_gemma":[0.999249,0.0004033946,0.00002987024,0.0001848872,0.0000535619,0.00007930753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003447011,0.000002191608,0.000005579186,0.0001030426,0.00001217239,0.000002197531,0.0000375756,0.002587732,0.00036864,0.0004044429,0.00001619894,0.9964568],"study_design_scores_gemma":[0.0003549526,0.0001363084,0.0001246163,0.0004569752,0.00003901435,0.00008783756,4.178722e-7,0.7715639,0.01237136,0.2020299,0.01223285,0.000601905],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007441084,0.0004565337,0.9960457,0.0004146646,0.0017353,0.0001871384,0.000005136814,0.0001646953,0.0009164251],"genre_scores_gemma":[0.1293404,0.0003051394,0.8683507,0.0007841702,0.000895196,0.00005661541,0.000003356965,0.00004120636,0.0002232019],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9958549,"threshold_uncertainty_score":0.7613649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376273093122532,"score_gpt":0.2931832349019598,"score_spread":0.2794205039707345,"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."}}