{"id":"W4206236031","doi":"10.21203/rs.3.rs-1157621/v1","title":"Genetic determinants of polygenic prediction accuracy within a population","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Jewish General Hospital; Public Health Agency; Compute Canada; National Institutes of Health; Public Health Agency of Canada; Cancer Research UK; McGill University","keywords":"Population; Polygenic risk score; Evolutionary biology; Geography; Econometrics; Computer science; Biology; Genetics; Demography; Economics; Sociology; Genotype; Single-nucleotide polymorphism; Gene","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":[0.001722668,0.0001949219,0.0003411112,0.0002410757,0.0002271518,0.00002115409,0.0004532663,0.0004912086,0.0001523717],"category_scores_gemma":[0.001780163,0.000203947,0.0002027689,0.000209157,0.00009486218,0.000002339583,0.001476436,0.0006521834,0.000006350958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244391,"about_ca_system_score_gemma":0.0004284619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337318,"about_ca_topic_score_gemma":0.0003799977,"domain_scores_codex":[0.9965966,0.001101223,0.0006644529,0.0006455253,0.0005516778,0.0004404759],"domain_scores_gemma":[0.9981745,0.00011587,0.0004112637,0.0008532683,0.0003431119,0.0001019916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007798674,0.0001070079,0.980724,0.0002754034,0.00008091559,0.000003437215,0.0001497292,0.008288225,0.005474007,0.00001208677,0.001338281,0.003468916],"study_design_scores_gemma":[0.0002457793,0.000508184,0.9932091,0.00006433958,0.00002420563,0.000007421812,0.000249541,0.002761337,0.0008251207,0.001001912,0.0009325223,0.0001704911],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963807,0.001551195,0.0002025037,0.00006608193,0.0003831061,0.0007665879,0.0004308098,0.00001353129,0.0002054113],"genre_scores_gemma":[0.9954574,0.0008347839,0.001326388,0.00001792105,0.0003248696,0.0003189421,0.001183665,0.00003997705,0.0004960819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01248514,"threshold_uncertainty_score":0.8316718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05468676686810255,"score_gpt":0.4054661693408798,"score_spread":0.3507794024727773,"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."}}