{"id":"W2110116210","doi":"10.1007/11424918_31","title":"Incorporating Evidence in Bayesian Networks with the Select Operator","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Bayesian network; Operator (biology); Probabilistic logic; Relational database; Bayesian probability; Knowledge base; Expert system; Artificial intelligence; Data mining; Theoretical computer science; Machine learning","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":[0.009529221,0.001339861,0.002305124,0.001837047,0.00086048,0.003648879,0.003012495,0.002335296,0.004305786],"category_scores_gemma":[0.0317179,0.001845575,0.001751654,0.00265661,0.003070127,0.00965831,0.003342251,0.004709854,0.0006407388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001561885,"about_ca_system_score_gemma":0.001513014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004387708,"about_ca_topic_score_gemma":0.004541645,"domain_scores_codex":[0.9961222,0.002614381,0.0001667532,0.0004308497,0.0005387059,0.0001271398],"domain_scores_gemma":[0.9745705,0.02282936,0.0007675076,0.0009243084,0.0006148171,0.0002935209],"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":[0.0001145247,0.00004058842,0.0004599242,0.0001836854,0.0001034368,0.0001061688,0.0001759919,0.2677264,0.000357533,0.6830136,0.001658523,0.04605967],"study_design_scores_gemma":[0.00001671344,0.00001260337,0.00005498712,0.00002380721,0.00002590088,0.00002263776,0.000009207981,0.4420338,0.0001552336,0.5566332,0.0009973679,0.00001448004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002757112,0.0005288461,0.9947639,0.0003379286,0.00002724,0.00001707028,0.00005874605,0.0000906191,0.001418696],"genre_scores_gemma":[0.2955961,0.003446547,0.6912973,0.0003969159,0.0005944508,0.0003742753,0.0004503183,0.0002937939,0.007550322],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009529221,"threshold_uncertainty_score":0.05039591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02517949841777687,"score_gpt":0.2484241444648888,"score_spread":0.2232446460471119,"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."}}