{"id":"W1973938029","doi":"10.3166/ria.21.555-587","title":"Réseaux GAI pour la prise de décision","year":2007,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003804384,0.0003881192,0.000354556,0.0002057547,0.0003135677,0.0004739392,0.001351462,0.0004250877,0.0004425469],"category_scores_gemma":[0.0004667025,0.0004322019,0.0002391359,0.0009761458,0.0003075761,0.00054401,0.0003789114,0.0007744405,0.00493858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002172956,"about_ca_system_score_gemma":0.0004877505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004161391,"about_ca_topic_score_gemma":0.00005098998,"domain_scores_codex":[0.9962413,0.0002815641,0.0008992965,0.0009113679,0.0003892813,0.001277153],"domain_scores_gemma":[0.9967892,0.0009690644,0.0002141222,0.001095543,0.000390401,0.0005416465],"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":[0.00002980912,0.0004616347,0.0001907364,0.0001208835,0.00001955359,0.0003985527,0.00486369,0.02855441,0.006000657,0.2803152,0.006795461,0.6722494],"study_design_scores_gemma":[0.00005047392,0.0001246523,0.0001217916,0.0005590009,0.00002282447,0.0003649826,0.0003972086,0.8110607,0.05785079,0.05611952,0.07286032,0.0004677305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008003311,0.005461398,0.9397501,0.007889947,0.001605675,0.0002104764,0.00000529085,0.0001898382,0.036884],"genre_scores_gemma":[0.8262997,0.0009717812,0.1028843,0.0007880167,0.0006243724,0.000009972055,0.000003168744,0.00004793247,0.06837084],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8368658,"threshold_uncertainty_score":0.999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07617905626167878,"score_gpt":0.3237514229988046,"score_spread":0.2475723667371258,"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."}}