{"id":"W1666386643","doi":"10.1214/lnms/1215540964","title":"The Practical Implementation of Bayesian Model Selection","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes-monograph series","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":433,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Selection (genetic algorithm); Computer science; Bayesian probability; Bayesian inference; Model selection; Artificial intelligence","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":[0.007438814,0.0009420296,0.0008635951,0.001096693,0.0007131029,0.002440417,0.002376778,0.001949661,0.01492764],"category_scores_gemma":[0.022786,0.0007092232,0.0008118892,0.001693792,0.001063058,0.002672937,0.002507488,0.002935016,0.007513294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009792406,"about_ca_system_score_gemma":0.001657338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002178834,"about_ca_topic_score_gemma":0.002473636,"domain_scores_codex":[0.9945735,0.003544949,0.0001285236,0.0003351254,0.001317271,0.0001006026],"domain_scores_gemma":[0.9952031,0.003426852,0.000108714,0.0006846087,0.0005196452,0.00005708199],"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":[0.0000307514,0.00005579373,0.0003614367,0.0001987526,0.00005572162,0.0001824681,0.0002543898,0.04337056,0.0009911014,0.5744089,0.02140414,0.358686],"study_design_scores_gemma":[0.00002942507,0.00002016703,0.0001876558,0.00009427246,0.00001600463,0.000214269,0.00005982038,0.1787152,0.001074912,0.763029,0.05652885,0.00003025464],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004423661,0.0002619112,0.9893081,0.0008747184,0.0000592233,0.00003315846,0.00004776636,0.0004215638,0.008551289],"genre_scores_gemma":[0.02616001,0.0008603861,0.9654472,0.0003924949,0.0001224515,0.0002272087,0.0001992333,0.0002337214,0.006357268],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01492764,"threshold_uncertainty_score":0.0499379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05280911275820354,"score_gpt":0.3770241510213588,"score_spread":0.3242150382631553,"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."}}