{"id":"W2040076368","doi":"10.2307/3316081","title":"On cross‐validation of Bayesian models","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bayesian probability; Cross-validation; Computer science; Sample (material); Variable-order Bayesian network; Model validation; Scheme (mathematics); Artificial intelligence; Machine learning; Bayesian inference; Data mining; Mathematics; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.07699727,0.001477366,0.002531961,0.002760754,0.001196451,0.00263288,0.004376382,0.003896384,0.003475804],"category_scores_gemma":[0.1832735,0.001599448,0.001428197,0.002227962,0.003775894,0.003618333,0.006237392,0.004907541,0.0007324552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002687504,"about_ca_system_score_gemma":0.002745714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01178874,"about_ca_topic_score_gemma":0.00768372,"domain_scores_codex":[0.9548934,0.0384897,0.0009945703,0.001847795,0.002886373,0.0008882721],"domain_scores_gemma":[0.7737916,0.2028378,0.002870546,0.009771235,0.00954277,0.001186092],"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":[0.0004231182,0.0001340685,0.003067032,0.0001654499,0.0004458013,0.0001125622,0.0001531721,0.7794878,0.0005636839,0.1333016,0.0030308,0.07911489],"study_design_scores_gemma":[0.00002125606,0.00003703214,0.000398236,0.00007472171,0.000021429,0.0000221016,0.00001043436,0.9538788,0.0002928259,0.04457337,0.0006536824,0.00001614313],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01092401,0.0007464379,0.9859848,0.0004545274,0.00006757986,0.00004820396,0.00005296826,0.0002071184,0.001514309],"genre_scores_gemma":[0.5751993,0.001320786,0.4144408,0.001202713,0.0005042786,0.0005228944,0.001046999,0.0004497206,0.005312602],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07699727,"threshold_uncertainty_score":0.4072053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08078842530196748,"score_gpt":0.3431410216912403,"score_spread":0.2623525963892728,"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."}}