{"id":"W2922001156","doi":"10.1101/574616","title":"Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Canadian Respiratory Research Network; McMaster University; Population Health Research Institute","funders":"Canadian Institutes of Health Research; Indian Council of Medical Research; McMaster University; Heart and Stroke Foundation of Canada","keywords":"Gestational diabetes; Heritability; Medicine; Demography; Logistic regression; Genome-wide association study; Obstetrics; Type 2 diabetes; Diabetes mellitus; Pregnancy; Genotype; Biology; Internal medicine; Genetics; Gestation; Endocrinology; Single-nucleotide polymorphism","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001095716,0.0003796364,0.0002468038,0.0006988788,0.0004217327,0.0006207281,0.0003244272,0.0003101415,0.002314051],"category_scores_gemma":[0.002587211,0.000232668,0.0008691574,0.001122936,0.0002950137,0.0002083137,0.0007111229,0.0005490088,0.0002698252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002551957,"about_ca_system_score_gemma":0.0003347069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02009048,"about_ca_topic_score_gemma":0.01441149,"domain_scores_codex":[0.9996951,0.0001106106,0.00003038366,0.00008325699,0.00004772301,0.00003300318],"domain_scores_gemma":[0.9987808,0.0003194196,0.0003503625,0.0002376325,0.0001283052,0.0001833905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001204711,0.000008372904,0.9975417,0.000008895594,0.0001338532,0.00006150746,0.0001529028,0.00008574147,0.0003371213,0.00004497232,0.000090125,0.001414347],"study_design_scores_gemma":[0.000006085706,0.00002880791,0.9984595,0.00001298302,0.00007995935,0.0001109501,0.0002535342,0.0007275419,0.00008997757,0.00008414535,0.0001423632,0.000004255814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989533,0.0001538702,0.0002048736,0.0000661982,0.000005859572,0.000003746901,0.0003121683,0.000004585208,0.0002953611],"genre_scores_gemma":[0.9993082,0.0000679185,0.0001802304,0.00001431509,0.000002962343,0.000004941951,0.0002721291,0.000002945879,0.0001462491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02009048,"threshold_uncertainty_score":0.03994709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01037778762195034,"score_gpt":0.2152164074650867,"score_spread":0.2048386198431364,"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."}}