{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009099979,0.0001036922,0.0002782865,0.0002298521,0.00006286849,0.00003960426,0.0001706364,0.00006609868,0.000167958],"category_scores_gemma":[0.001454434,0.0000925705,0.00007233016,0.0001097296,0.0000740635,0.0000859017,0.000004577825,0.0001669815,1.303167e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100422,"about_ca_system_score_gemma":0.0005311182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004666402,"about_ca_topic_score_gemma":0.002883988,"domain_scores_codex":[0.9987484,0.0001094849,0.0006263593,0.00007666587,0.0002409,0.0001981549],"domain_scores_gemma":[0.9978692,0.0005113202,0.0004895694,0.0001942742,0.0005441423,0.0003914954],"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":[0.00007554441,0.00006697807,0.002438015,0.0001100577,0.00008351271,0.0005393799,0.001375818,0.003408002,0.00008916835,0.9366177,0.04148597,0.0137098],"study_design_scores_gemma":[0.001083148,0.000687454,0.0004004288,0.0002360294,0.0001061987,0.0002676071,0.0002894053,0.01080597,0.001302578,0.9785624,0.005971427,0.0002873228],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.142052,0.00004499066,0.8484206,0.00009595636,0.000346389,0.00007452135,0.0002550784,0.000002475332,0.008707963],"genre_scores_gemma":[0.7909229,0.00002142708,0.2081261,0.00008329198,0.00009554394,5.806762e-7,0.000005046636,0.00002159624,0.0007235296],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6488708,"threshold_uncertainty_score":0.3774915,"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."}}