{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001051528,0.0000927991,0.000346664,0.00004574003,0.00006683193,0.000001566551,0.0001038631,0.00008085748,0.000009309366],"category_scores_gemma":[0.000164311,0.00008254393,0.0001755248,0.0001491766,0.00007853344,0.000001875845,0.0000477711,0.00002291386,9.250809e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007068381,"about_ca_system_score_gemma":0.00006050488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009144112,"about_ca_topic_score_gemma":0.000002002516,"domain_scores_codex":[0.9992232,0.00006149572,0.0003035723,0.0002190161,0.00005439795,0.0001382979],"domain_scores_gemma":[0.9994034,0.00005733432,0.000221801,0.000117114,0.0001472698,0.00005311774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001852356,0.0002387151,0.07154294,0.00004073037,0.001528287,5.810334e-7,0.00006025838,0.3594527,0.5638537,0.001788333,0.0006068604,0.0007016243],"study_design_scores_gemma":[0.0004283299,0.0002314493,0.9646224,0.000002513422,0.000517317,0.000001367889,0.00001819265,0.02575101,0.00596883,0.001224149,0.001047583,0.0001867964],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803364,0.003710455,0.01503062,0.00002690944,0.00002529506,0.0001313543,0.0007215301,0.000003738556,0.0000137419],"genre_scores_gemma":[0.9908959,0.001172297,0.005233041,0.0000831558,0.00002231687,0.00002116408,0.002535988,0.000007013431,0.00002915603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8930795,"threshold_uncertainty_score":0.3366044,"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."}}