{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009630245,0.001236597,0.001921338,0.001927305,0.00254576,0.009741697,0.002296032,0.008676507,0.03941471],"category_scores_gemma":[0.02431371,0.0003934486,0.001250194,0.001733324,0.004245964,0.0070843,0.00218624,0.009435514,0.009835051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006899184,"about_ca_system_score_gemma":0.004913219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009836551,"about_ca_topic_score_gemma":0.00667023,"domain_scores_codex":[0.9931418,0.003533544,0.0001795389,0.0009091193,0.001819314,0.0004167639],"domain_scores_gemma":[0.9798384,0.01353848,0.0003908856,0.001442002,0.003622718,0.001167543],"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":[0.0002682327,0.00009836369,0.0004510494,0.0004070429,0.00007607426,0.0001929717,0.0004364714,0.005911659,0.000519446,0.6911214,0.1588161,0.1417013],"study_design_scores_gemma":[0.00006854028,0.0000744119,0.000816609,0.0005685218,0.00003505164,0.0001739849,0.0005908927,0.01396662,0.0005167397,0.443474,0.5396535,0.00006106653],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008322736,0.1186532,0.07148729,0.5049005,0.03199999,0.0001087936,0.0005159277,0.0005783168,0.2634333],"genre_scores_gemma":[0.3158438,0.1170973,0.06061504,0.04340294,0.05733451,0.0003853985,0.001028819,0.000651164,0.403641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03941471,"threshold_uncertainty_score":0.1318553,"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."}}