{"id":"W4313492671","doi":"10.1016/j.xgen.2022.100241","title":"Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts","year":2023,"lang":"en","type":"article","venue":"Cell Genomics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"Moonshot Research and Development Program; National Institute of General Medical Sciences; National Institute of Mental Health; National Heart, Lung, and Blood Institute; National Institute on Aging; Faculty of Medicine and Health, University of Sydney; St. Olavs Hospital Universitetssykehuset i Trondheim; Japan Society for the Promotion of Science; Medical Research Council; National Institutes of Health; Eesti Teadusagentuur; Fakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige Universitet; Japan Agency for Medical Research and Development; European Commission; National Human Genome Research Institute; Wellcome Trust; Stiftelsen Kristian Gerhard Jebsen; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)","keywords":"Biobank; Heritability; Precision medicine; Genome-wide association study; Linkage disequilibrium; Genetic association; Medicine; Bioinformatics; Biology; Genetics; Single-nucleotide polymorphism","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0992032,0.002275,0.002634736,0.008728894,0.001333628,0.007992073,0.002489823,0.001298654,0.005770392],"category_scores_gemma":[0.1976913,0.001336534,0.003229169,0.00861157,0.001929858,0.005392874,0.007267245,0.004160171,0.001974262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001177398,"about_ca_system_score_gemma":0.002807019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006804524,"about_ca_topic_score_gemma":0.009393504,"domain_scores_codex":[0.9642094,0.02557383,0.003165758,0.004564512,0.002028191,0.0004583519],"domain_scores_gemma":[0.8854437,0.05950014,0.009587212,0.03534881,0.008513869,0.001606251],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008020147,0.0001691082,0.4784396,0.001634303,0.01740469,0.0005468598,0.005746697,0.01727535,0.003308338,0.04926526,0.06027065,0.3651372],"study_design_scores_gemma":[0.0005075114,0.000510267,0.3290915,0.003199382,0.0062191,0.0007714687,0.003510099,0.04178928,0.004250064,0.5047082,0.10496,0.0004831463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.114549,0.007671746,0.8128176,0.01822587,0.0009873636,0.0008135801,0.02805741,0.004673948,0.01220352],"genre_scores_gemma":[0.4268583,0.003049494,0.5419385,0.005360652,0.0006660044,0.001097187,0.01731918,0.002389131,0.001321477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9007968,"threshold_uncertainty_score":0.5246429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05915114020890409,"score_gpt":0.366940908295321,"score_spread":0.3077897680864169,"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."}}