{"id":"W1514470448","doi":"10.7939/r3610vr65","title":"Discriminative Model Selection for Belief Net Structures","year":2004,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Discriminative model; Artificial intelligence; Computer science; Model selection; Machine learning; Bayesian information criterion; Likelihood function; Selection (genetic algorithm); Graphical model; Pattern recognition (psychology); Estimation theory; Algorithm","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":[0.00006722706,0.0000877691,0.00007563158,0.0000416779,0.0001180992,0.00009529906,0.0002940053,0.00004360324,0.000003008258],"category_scores_gemma":[0.00001403356,0.00007042657,0.00003668507,0.0001155318,0.00001792515,0.0003104348,0.00004736934,0.00006507275,0.000004635396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003778503,"about_ca_system_score_gemma":0.00008879726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006225681,"about_ca_topic_score_gemma":0.00004128734,"domain_scores_codex":[0.999361,0.000007300388,0.00009956706,0.0002483058,0.0001048972,0.0001789365],"domain_scores_gemma":[0.9996684,0.00001636759,0.00002775972,0.0001416081,0.00009435338,0.00005154566],"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":[0.000002350282,0.00001528005,0.000003070377,0.000003648023,0.00000367693,8.76303e-8,0.0004201129,0.1174096,0.0006705947,0.8712837,0.000269654,0.009918216],"study_design_scores_gemma":[0.0001255626,0.00005294096,0.00002850764,0.000002744765,0.000001969448,0.00000213661,0.000008535363,0.5418299,0.005898285,0.4519636,0.00001957754,0.00006613698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003783107,0.00001347826,0.9929976,0.0009397735,0.00008108422,0.0001086174,0.000001982765,0.0001698525,0.00190445],"genre_scores_gemma":[0.6292688,0.000001739658,0.3701079,0.0003169339,0.00002293902,0.00001381134,0.000001424803,0.000003336884,0.0002630598],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6254857,"threshold_uncertainty_score":0.2871912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03535879302562537,"score_gpt":0.2878144802364724,"score_spread":0.252455687210847,"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."}}