{"id":"W3087920238","doi":"10.1101/2020.09.22.20198937","title":"Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Impact; Hamilton Health Sciences; University of Toronto; McMaster University; Population Health Research Institute","funders":"","keywords":"Genome-wide association study; Type 2 diabetes; Genetics; Genetic association; Biology; Evolutionary biology; Population stratification; Population; Translation (biology); 1000 Genomes Project; Computational biology; Transferability; Genome; Genetic genealogy; Gene; Genotype; Single-nucleotide polymorphism; Medicine; Diabetes mellitus; Computer science; Environmental health; Machine learning","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":[0.01319434,0.0007590739,0.001276756,0.00157261,0.001107197,0.003225862,0.0006168584,0.0006897926,0.002924732],"category_scores_gemma":[0.01822011,0.0005134333,0.001389929,0.00218881,0.001507341,0.001060714,0.004306818,0.001809936,0.0004547412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285746,"about_ca_system_score_gemma":0.0006994788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003154738,"about_ca_topic_score_gemma":0.003943494,"domain_scores_codex":[0.992516,0.005004961,0.0003178396,0.001467644,0.0004471791,0.0002464798],"domain_scores_gemma":[0.9876845,0.006048033,0.000695421,0.004414271,0.0006282293,0.0005294859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002202883,0.0001770424,0.6544801,0.0007872661,0.009900559,0.002080413,0.006225973,0.01366452,0.08136653,0.0196691,0.003399889,0.2060457],"study_design_scores_gemma":[0.0003319216,0.0005983342,0.8147981,0.0005435382,0.005586401,0.002221437,0.002801015,0.02879863,0.01746864,0.08636082,0.04029537,0.0001958567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.888625,0.004311614,0.09642522,0.002133216,0.0002129166,0.00005476256,0.002158045,0.0003566132,0.005722729],"genre_scores_gemma":[0.9773906,0.0007759824,0.01927633,0.0004298509,0.000115818,0.00002815389,0.001253376,0.0001329972,0.0005970512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01319434,"threshold_uncertainty_score":0.06977916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05905478832366751,"score_gpt":0.3059960615713404,"score_spread":0.2469412732476729,"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."}}