{"id":"W2103834654","doi":"","title":"Bayesian Pedigree Analysis using Measure Factorization","year":2012,"lang":"en","type":"article","venue":"","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pedigree chart; Computer science; Inference; Graphical model; Bayesian network; Estimator; Bayesian inference; Machine learning; Bayesian probability; Artificial intelligence; Theoretical computer science; Data mining; Computational biology; Mathematics; Statistics; Biology; Genetics","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":[0.004566881,0.0008311578,0.00132991,0.002817714,0.0007766607,0.001771142,0.00203423,0.001039663,0.005846196],"category_scores_gemma":[0.02006448,0.0007482094,0.001519536,0.002863452,0.001177625,0.002216795,0.001964747,0.001826573,0.001432669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001708475,"about_ca_system_score_gemma":0.00252826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01609173,"about_ca_topic_score_gemma":0.01351059,"domain_scores_codex":[0.9975509,0.001392362,0.00009675122,0.0003974571,0.0004027474,0.0001597555],"domain_scores_gemma":[0.9918965,0.006018537,0.0006640869,0.0006148545,0.0006083442,0.0001977179],"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":[0.00006272196,0.00005571466,0.003970613,0.0001611149,0.0002339707,0.0001824499,0.0002495197,0.2998966,0.0005491276,0.5381339,0.008249544,0.1482549],"study_design_scores_gemma":[0.00002141728,0.00001363888,0.0006413994,0.00003547663,0.00002637536,0.00007688015,0.00002297238,0.6560218,0.00008704221,0.338697,0.004334232,0.00002171379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001296981,0.0002873384,0.9972838,0.000122476,0.0000157621,0.00002123113,0.0001408172,0.0001521768,0.0006794183],"genre_scores_gemma":[0.1855862,0.002244872,0.8030571,0.0003341606,0.0002927125,0.0004122911,0.001762417,0.0002596833,0.006050454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01609173,"threshold_uncertainty_score":0.03199613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672552935009802,"score_gpt":0.287333936074498,"score_spread":0.2606084067243999,"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."}}