{"id":"W4211247877","doi":"10.1007/978-1-4471-7452-3_22","title":"Probabilistic and Bayesian Networks","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Variable-order Bayesian network; Probabilistic logic; Bayesian network; Computer science; Probabilistic relevance model; Bayesian programming; Artificial intelligence; Machine learning; Dynamic Bayesian network; Bayesian probability; Maximization; Graphical model; Statistical model; Bayesian inference; Mathematics; Probabilistic analysis of algorithms; Mathematical optimization","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009142207,0.001494123,0.0009761825,0.002103283,0.0008685312,0.003893833,0.001198958,0.00202902,0.04679585],"category_scores_gemma":[0.003659824,0.0007105322,0.0004692027,0.003289294,0.002453485,0.005401328,0.001421211,0.003089906,0.01844484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002136588,"about_ca_system_score_gemma":0.001515591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003282487,"about_ca_topic_score_gemma":0.004359189,"domain_scores_codex":[0.999209,0.0002485455,0.00002476978,0.0001344545,0.000351416,0.00003190083],"domain_scores_gemma":[0.9991474,0.0005834778,0.00003073605,0.00008843043,0.0001177236,0.00003229647],"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":[0.000004725805,0.00001773315,0.00004151882,0.0001495179,0.000009334045,0.00002844331,0.0001150923,0.001857405,0.00008456458,0.7980306,0.1161558,0.08350533],"study_design_scores_gemma":[0.000001622325,0.000003616247,0.00006943273,0.0001188317,0.000004516564,0.00005556484,0.00003282605,0.002132783,0.00005040338,0.6131253,0.3843973,0.000007813306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0006535294,0.06973753,0.1445665,0.008345026,0.003638022,0.0000677346,0.0005428135,0.0004644004,0.7719846],"genre_scores_gemma":[0.03292136,0.0804549,0.04749546,0.002996972,0.00541159,0.0002508523,0.0008488084,0.0005560254,0.8290641],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04679585,"threshold_uncertainty_score":0.1565477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875039331605164,"score_gpt":0.2164325483584164,"score_spread":0.1976821550423648,"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."}}