{"id":"W1977773138","doi":"10.1002/gepi.21772","title":"A Variational Bayes Discrete Mixture Test for Rare Variant Association","year":2013,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Human Genome Research Institute; National Cancer Institute; National Heart, Lung, and Blood Institute","keywords":"Bayes' theorem; Exome; Inference; Missense mutation; Genetic association; Bayes factor; Genome-wide association study; Genetics; Exome sequencing; Computational biology; Biology; Computer science; Bayesian probability; Gene; Statistics; Phenotype; Mathematics; Genotype; Single-nucleotide polymorphism; Artificial intelligence","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":[0.01364305,0.001009081,0.002353823,0.001935644,0.001093404,0.001912792,0.003863154,0.002158459,0.006985193],"category_scores_gemma":[0.05912536,0.001033379,0.001931059,0.001636553,0.002725296,0.002393432,0.00277373,0.003170221,0.0009329218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151429,"about_ca_system_score_gemma":0.003067297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00765829,"about_ca_topic_score_gemma":0.004587177,"domain_scores_codex":[0.9922698,0.004944476,0.0002925479,0.001286376,0.0009219613,0.0002849359],"domain_scores_gemma":[0.9635433,0.03281857,0.0008988832,0.001065325,0.0011164,0.0005575558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006971461,0.0001597486,0.02026922,0.0003036576,0.0006146955,0.0004890919,0.0003628157,0.4253061,0.002273464,0.3094087,0.00790144,0.2322139],"study_design_scores_gemma":[0.00007655457,0.00005573911,0.0008197984,0.00002305969,0.00003259439,0.0001070666,0.00002061142,0.9397786,0.0003152747,0.05730594,0.001440408,0.00002436206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009721367,0.000298441,0.9875183,0.0005369774,0.00009057499,0.0001499331,0.0002091684,0.0003836454,0.001091641],"genre_scores_gemma":[0.3348376,0.0004867631,0.6558137,0.0008909343,0.0003181176,0.0008471607,0.001482174,0.0003800387,0.004943434],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01364305,"threshold_uncertainty_score":0.07215226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341434885352244,"score_gpt":0.271512423643974,"score_spread":0.2580980747904516,"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."}}