{"id":"W2505877522","doi":"10.4018/978-1-60566-663-1.ch010","title":"Overview of Bayesian Belief Network","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Frequentist inference; Bayesian network; Bayesian probability; Computer science; Frequentist probability; Rigour; Bayesian statistics; Artificial intelligence; Bayesian inference; Machine learning; Prior probability; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002166432,0.0004841996,0.0007005361,0.00005129211,0.00008799558,0.0001116791,0.001528994,0.0004765799,0.00002258195],"category_scores_gemma":[0.000007149841,0.0004815641,0.0003222022,0.00005105149,0.000085162,0.00008252981,0.0003392648,0.000360792,0.00009859321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020163,"about_ca_system_score_gemma":0.0003251194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003900696,"about_ca_topic_score_gemma":0.00002989973,"domain_scores_codex":[0.9976514,0.00003095355,0.0006173585,0.0006831029,0.0005342169,0.0004829477],"domain_scores_gemma":[0.9979857,0.0000317843,0.0003839422,0.001210068,0.0001701786,0.0002183128],"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":[0.000004166935,0.000007540169,0.000001853756,0.00003331167,0.00003531755,0.00002837682,0.00001771489,0.00006400192,0.000001597351,0.8689395,0.003096742,0.1277699],"study_design_scores_gemma":[0.0001420155,0.0001689317,0.00001843301,0.0007743865,0.00003995508,0.00003817165,3.455851e-7,0.00197069,0.00001227066,0.9712368,0.02512792,0.0004700647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000001336338,0.003308743,0.2026742,0.0001076205,0.0003559161,0.0001546194,0.00002066683,0.0001836978,0.7931932],"genre_scores_gemma":[0.3129488,0.0009023934,0.2496489,0.01442537,0.003550425,0.0000394333,0.00002392626,0.0002513986,0.4182093],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3749839,"threshold_uncertainty_score":0.9997636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03891703990534051,"score_gpt":0.2718792423349894,"score_spread":0.2329622024296489,"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."}}