{"id":"W4408884871","doi":"10.1093/bib/bbaf125","title":"MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics.","year":2025,"lang":"en","type":"article","venue":"PubMed","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute on Aging","keywords":"Endophenotype; Genome-wide association study; Atlas (anatomy); Association (psychology); Genetic association; Computer science; Computational biology; Biology; Artificial intelligence; Genetics; Psychology; Single-nucleotide polymorphism; Gene; Genotype; Neuroscience","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":[0.002992025,0.000956647,0.001244353,0.005095393,0.0005314927,0.001980088,0.001830489,0.001004006,0.04180848],"category_scores_gemma":[0.02666833,0.0007122583,0.001418398,0.007819662,0.0004361978,0.001148703,0.003044428,0.001068425,0.009489339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006145718,"about_ca_system_score_gemma":0.002025442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005663581,"about_ca_topic_score_gemma":0.00878644,"domain_scores_codex":[0.9975358,0.0008085847,0.0002803429,0.0008501664,0.0004016501,0.0001234739],"domain_scores_gemma":[0.983068,0.009969817,0.002208168,0.003149099,0.00103847,0.00056653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001689768,0.0001096237,0.1334088,0.005180567,0.004048397,0.001564199,0.001271898,0.008212278,0.009352051,0.02788785,0.6280947,0.1791799],"study_design_scores_gemma":[0.0008211243,0.0002855986,0.1932212,0.0008396849,0.002285722,0.003293279,0.0003996832,0.01217324,0.007250603,0.07610235,0.7030402,0.0002874023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02591993,0.001664485,0.1075408,0.0007627586,0.0001649586,0.0002096828,0.8371463,0.02007679,0.006514297],"genre_scores_gemma":[0.1737694,0.00199593,0.1394121,0.000982821,0.0001831745,0.002364738,0.6683795,0.006831023,0.006081272],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04180848,"threshold_uncertainty_score":0.1398633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02262342748156436,"score_gpt":0.2687962228457488,"score_spread":0.2461727953641844,"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."}}