{"id":"W2020139178","doi":"10.1109/iat.2006.82","title":"Iterative Compilation of Multiagent Probabilistic Graphical Models","year":2006,"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":"Dalhousie University","funders":"","keywords":"Tree traversal; Computer science; Graphical model; Probabilistic logic; Tree (set theory); Theoretical computer science; Set (abstract data type); Synchronization (alternating current); Inference; Bayesian network; Domain (mathematical analysis); Distributed computing; Artificial intelligence; Algorithm; Programming language; Channel (broadcasting)","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":[0.0001080363,0.00007327359,0.0001015997,0.00005504439,0.00003772862,0.00004212654,0.0002337868,0.00003658591,0.000007215599],"category_scores_gemma":[0.000006342354,0.00005931955,0.00003848624,0.000197073,0.00004286699,0.0002588884,0.00005379845,0.00005780223,0.000005645586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001075232,"about_ca_system_score_gemma":0.00002549333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008179051,"about_ca_topic_score_gemma":0.00001591318,"domain_scores_codex":[0.9992718,0.00003801734,0.0002127987,0.000199762,0.0001651479,0.0001125129],"domain_scores_gemma":[0.9995251,0.00004674757,0.00005063625,0.0002166439,0.0001299577,0.00003096652],"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":[0.000001730348,0.00007534221,0.0001319887,0.000006316629,0.000002291801,7.409931e-7,0.0001227373,0.0613915,0.000684639,0.9360166,0.0001191038,0.001446975],"study_design_scores_gemma":[0.00007997696,0.00002765537,0.0009609372,0.000008317495,0.000001534237,0.00000125585,0.000002071699,0.7425097,0.0009831841,0.2553618,0.000007097601,0.00005654177],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01981387,0.00002464209,0.9736747,0.0002130918,0.00004475419,0.00009064312,0.000002255468,0.00008381475,0.006052205],"genre_scores_gemma":[0.9016681,0.000001097585,0.0981609,0.00004826772,0.0000131908,0.000005929096,0.000004010133,0.000002247153,0.00009626744],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8818542,"threshold_uncertainty_score":0.2418981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02916799806684217,"score_gpt":0.2475431947444966,"score_spread":0.2183751966776544,"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."}}