{"id":"W2132917408","doi":"10.1109/ictai.2009.32","title":"MA-DBN: Modeling Cooperative Agents for Approximate Online Monitoring","year":2009,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Bounded function; Dynamic Bayesian network; Domain (mathematical analysis); Multi-agent system; Distributed computing; Mathematical optimization; Artificial intelligence; Theoretical computer science; Bayesian network; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001604632,0.0001503411,0.0001556909,0.00005426951,0.0001564847,0.0001936257,0.0005498728,0.0000604884,0.000004028927],"category_scores_gemma":[0.00002288872,0.0001283736,0.0000553852,0.0001715239,0.000008592279,0.0004180239,0.00006653331,0.0001131469,0.00001051873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002805808,"about_ca_system_score_gemma":0.00004531047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009588311,"about_ca_topic_score_gemma":9.865445e-7,"domain_scores_codex":[0.998898,0.00001894451,0.0002208725,0.0003810011,0.0001625773,0.0003186226],"domain_scores_gemma":[0.9993367,0.00002429678,0.00003455415,0.0003237529,0.0001788025,0.0001018455],"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":[0.00004273636,0.000575157,0.0000994498,0.00003758776,0.00004911853,0.00001415208,0.002054107,0.3154833,0.005933804,0.3904142,0.001008823,0.2842876],"study_design_scores_gemma":[0.0002332412,0.0001075599,0.00002102782,0.00003025402,0.000003552372,0.00000313584,0.00004129906,0.9823684,0.002205428,0.01474915,0.00006470751,0.0001723072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02513015,0.00006479306,0.9723194,0.0009253864,0.0002222967,0.0001745005,0.000003730691,0.0002748691,0.0008848532],"genre_scores_gemma":[0.6982327,0.00001827676,0.3007013,0.0003935705,0.0001140128,0.000009762001,0.000003966858,0.000005406555,0.0005210368],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6731025,"threshold_uncertainty_score":0.5234923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09176539198560778,"score_gpt":0.3311457269745618,"score_spread":0.239380334988954,"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."}}