{"id":"W2103226344","doi":"10.1152/physiolgenomics.90247.2008","title":"Prioritization of candidate disease genes for metabolic syndrome by computational analysis of its defining phenotypes","year":2008,"lang":"en","type":"article","venue":"Physiological Genomics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics; University of Ottawa","funders":"","keywords":"Biology; Candidate gene; Genetics; Disease; Genetic linkage; Gene; Phenotype; Population; Quantitative trait locus; Computational biology; Bioinformatics; Medicine; Internal medicine","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":[0.001542054,0.0009385814,0.001289357,0.002033403,0.0005089639,0.001340242,0.0008696094,0.0005857537,0.001799301],"category_scores_gemma":[0.005614867,0.0004419972,0.001281849,0.000861698,0.0004230183,0.0003688927,0.000816549,0.0005566526,0.0001480976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006513517,"about_ca_system_score_gemma":0.00188724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008830724,"about_ca_topic_score_gemma":0.01039151,"domain_scores_codex":[0.9996119,0.0002281184,0.00002564788,0.00005014073,0.00004446215,0.00003976727],"domain_scores_gemma":[0.9967648,0.00274312,0.0001469158,0.00007421424,0.0001642735,0.0001068011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001075286,0.0002917768,0.07524657,0.0001714073,0.0004572812,0.0007285747,0.0001396404,0.8802134,0.002756026,0.005590416,0.001953296,0.0313763],"study_design_scores_gemma":[0.00009337347,0.00003573626,0.002836589,0.000005815569,0.00007230193,0.0000645971,0.00004102867,0.9926692,0.0003096113,0.003654947,0.0002075467,0.000009178669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8249174,0.0003558577,0.1675347,0.001457642,0.0000488219,0.0002044476,0.001667428,0.001173724,0.002640097],"genre_scores_gemma":[0.913447,0.0001552987,0.08279478,0.0002663145,0.00003772527,0.0002073913,0.002554376,0.00006992881,0.0004671369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008830724,"threshold_uncertainty_score":0.01755863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.019992955202487,"score_gpt":0.2648458832679594,"score_spread":0.2448529280654724,"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."}}