{"id":"W3182648508","doi":"10.1007/s00125-021-05491-7","title":"Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control","year":2021,"lang":"en","type":"article","venue":"Diabetologia","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec; Montreal Heart Institute; Public Health Ontario; Ontario Institute for Cancer Research; Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Université de Montréal; Canada Research Chairs; Ministère de l'Économie, de l’Innovation et des Exportations du Québec; British Heart Foundation; Canadian Institutes of Health Research; National Institute for Health and Care Research; Québec Consortium for Drug Discovery; Institut de Valorisation des Données; Medical Research Council; Institut de Cardiologie de Montréal; Servier","keywords":"Medicine; Diabetes mellitus; Internal medicine; Logistic regression; Type 2 diabetes; Blood pressure; Biobank; Framingham Risk Score; Bioinformatics; Endocrinology; Disease; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003658086,0.0001576596,0.0002692761,0.0000377395,0.0001503669,0.00002373786,0.0001045248,0.0001864589,0.000005156629],"category_scores_gemma":[0.003303646,0.0001336395,0.00005395493,0.00008085842,0.0001435713,0.000002527313,0.0001801062,0.0001059945,0.000003660071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002825902,"about_ca_system_score_gemma":0.00005654757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001178563,"about_ca_topic_score_gemma":0.00002946956,"domain_scores_codex":[0.998567,0.000455657,0.0002062779,0.0004404677,0.00003940955,0.0002911909],"domain_scores_gemma":[0.9988114,0.0003362556,0.00009949993,0.0003544177,0.0002664979,0.0001319534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005664062,0.00003748362,0.6689168,0.000006690823,0.0004197013,0.000001023954,0.00008621221,0.00003423415,0.3278808,0.00002906389,0.001247694,0.001283636],"study_design_scores_gemma":[0.0007019386,0.0003107021,0.9659451,0.000009307037,0.0002033129,0.000009791807,0.0001980587,0.0002601386,0.02807776,0.0003203327,0.003806684,0.0001569062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981505,0.01502644,0.0004799559,0.002226142,0.00006005597,0.0002224605,0.0004155033,0.0000171282,0.00004736209],"genre_scores_gemma":[0.9962147,0.0005049562,0.0007321952,0.002216027,0.00004400512,0.0000794924,0.00009411715,0.00001319177,0.0001012896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.299803,"threshold_uncertainty_score":0.5449662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00633542172268734,"score_gpt":0.2263784593796591,"score_spread":0.2200430376569718,"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."}}