{"id":"W1997430148","doi":"10.3166/ria.18.383-410","title":"Un algorithme accéléré d'échantillonnage bayésien pour le modèle CART","year":2004,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mod; Cart; Mathematics; Combinatorics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003192523,0.001580183,0.002121204,0.001570034,0.001441474,0.002897704,0.001587007,0.002849437,0.01179235],"category_scores_gemma":[0.01150653,0.001342205,0.002097512,0.001800798,0.00171555,0.002730055,0.00170853,0.00484524,0.004149598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00146889,"about_ca_system_score_gemma":0.00185879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01861818,"about_ca_topic_score_gemma":0.0161736,"domain_scores_codex":[0.9975522,0.0008653936,0.0001026093,0.0006265462,0.0006743919,0.0001788943],"domain_scores_gemma":[0.9953656,0.00355104,0.0000906689,0.0003518869,0.0005322435,0.0001084988],"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":[0.0008209533,0.000103726,0.001660164,0.0003268807,0.0003017024,0.0002050322,0.0003472315,0.2810273,0.005776487,0.1583724,0.01335514,0.537703],"study_design_scores_gemma":[0.00007037187,0.00008052831,0.0006163754,0.00007257442,0.00005771147,0.0001156652,0.00003615675,0.9092757,0.002225508,0.07284528,0.01456487,0.00003933112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003618415,0.0008637309,0.9924769,0.0003055053,0.0002065396,0.00003467692,0.0001076605,0.0004858116,0.001900765],"genre_scores_gemma":[0.07379172,0.001682724,0.908664,0.0003277214,0.0004415874,0.0002994531,0.0005884125,0.0004789649,0.01372542],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01861818,"threshold_uncertainty_score":0.03944939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06497506700784612,"score_gpt":0.2834681431845764,"score_spread":0.2184930761767303,"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."}}