{"id":"W2127426313","doi":"10.1109/69.929898","title":"Constructing the dependency structure of a multiagent probabilistic network","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Dependency (UML); Probabilistic logic; Computer science; Cover (algebra); Graphical model; Representation (politics); Theoretical computer science; Domain (mathematical analysis); Dependency graph; Conditional probability; Artificial intelligence; Data mining; Mathematics; Graph","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":[0.0001307895,0.0001177266,0.0001216713,0.00004474395,0.0001167016,0.0000524777,0.0006049273,0.00004752879,0.000008143611],"category_scores_gemma":[0.00001016003,0.00008940815,0.00002285789,0.0002703344,0.00003234433,0.0002352226,0.00001625177,0.0002183403,0.000002629609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001456524,"about_ca_system_score_gemma":0.00003652559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001400424,"about_ca_topic_score_gemma":0.00007123351,"domain_scores_codex":[0.9992467,0.00002284001,0.0001821736,0.0002773891,0.00008849594,0.0001823873],"domain_scores_gemma":[0.9990463,0.0001565802,0.00003337226,0.0006642294,0.00004301067,0.00005646831],"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":[0.00001384069,0.0001099509,0.0001240198,0.0001568405,0.0001016242,0.00001039945,0.001086376,0.4699442,0.002311534,0.01524836,0.000118291,0.5107746],"study_design_scores_gemma":[0.0001287372,0.0000273814,0.00004999018,0.00007752793,0.00001970278,0.00006973524,0.00002334272,0.9977737,0.001068552,0.0004507422,0.0001934179,0.0001171447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01197128,0.0003896591,0.9868647,0.00004464524,0.0004407915,0.00009753496,0.0000304468,0.00007776269,0.00008311037],"genre_scores_gemma":[0.9776151,0.00007011861,0.02222091,0.00001058777,0.00005377846,0.000003689825,0.000003000656,0.000007091047,0.00001575361],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9656438,"threshold_uncertainty_score":0.3645959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0310304745145064,"score_gpt":0.2611466064437121,"score_spread":0.2301161319292057,"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."}}