{"id":"W2114563530","doi":"10.1023/a:1013916107446","title":"Bayesian Treed Models","year":2002,"lang":"en","type":"article","venue":"Machine Learning","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":184,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; University of Texas at Austin; University of Chicago; National Science Foundation","keywords":"Partition (number theory); Simple (philosophy); Computer science; Bayesian probability; Parametric statistics; Artificial neural network; Parametric model; Mathematics; Tree (set theory); Set (abstract data type); Algorithm; Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000248045,0.0001060489,0.0001745489,0.00004088904,0.0001097405,0.00003061681,0.0001007145,0.0000440734,0.003052751],"category_scores_gemma":[0.001313519,0.00008810879,0.00004353854,0.0001021274,0.00002516547,0.00004818414,0.00003820131,0.0002633283,0.00006754662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000127976,"about_ca_system_score_gemma":0.00000230166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003408837,"about_ca_topic_score_gemma":0.000006663031,"domain_scores_codex":[0.999162,0.0001563325,0.0001769251,0.0001583534,0.0001438696,0.0002025131],"domain_scores_gemma":[0.9990478,0.0006519508,0.00005637268,0.0001467667,0.00002278004,0.00007433942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007556207,0.0000944123,0.001983815,0.00005375585,0.00002292194,0.00002115015,0.001077591,0.0007153359,0.0001924108,0.7499011,0.001531503,0.2443985],"study_design_scores_gemma":[0.0001384856,0.00004263429,0.00006342103,0.00001262474,0.000009234104,0.000004278733,0.0000159365,0.648652,0.00002167386,0.3494644,0.001487349,0.0000878927],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003192803,0.00009624543,0.8868608,0.000267501,0.00004458423,0.0000588677,0.000002962528,0.0001499663,0.1093263],"genre_scores_gemma":[0.6226776,0.00001073324,0.372422,0.00008846606,0.00005054062,0.000005444999,0.000001258863,0.00002127133,0.004722672],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6479367,"threshold_uncertainty_score":0.9978586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184072395273905,"score_gpt":0.3423309401831147,"score_spread":0.2239237006557242,"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."}}