{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003352292,0.0004230794,0.0003967843,0.000847687,0.0003933091,0.0009228398,0.0003875229,0.0004675114,0.001927334],"category_scores_gemma":[0.01003105,0.0002043239,0.0006304639,0.0008519937,0.0007548634,0.0002989515,0.0005725136,0.0007042999,0.0001993522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001907378,"about_ca_system_score_gemma":0.000271731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005812868,"about_ca_topic_score_gemma":0.003421671,"domain_scores_codex":[0.9972344,0.001390315,0.0001745079,0.000664781,0.0003433259,0.0001926567],"domain_scores_gemma":[0.98729,0.008811311,0.001650581,0.001406573,0.0004750974,0.0003664834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000173352,0.00002365797,0.9910315,0.000008205027,0.0005110943,0.0001746476,0.0001433179,0.001460001,0.002396251,0.0001562392,0.00009758939,0.003824146],"study_design_scores_gemma":[0.000006996052,0.0000523361,0.9928297,0.000004321976,0.00008387175,0.0001930166,0.00004846525,0.006065166,0.0002839066,0.0003390327,0.00008349205,0.00000966922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975296,0.00008794866,0.00201024,0.00003460997,0.000004020078,0.000003396596,0.000147897,0.00001472119,0.0001675624],"genre_scores_gemma":[0.9995918,0.0000124629,0.0002481754,0.000005776831,0.000003633572,0.000001988014,0.00008657668,0.000003612512,0.0000460666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005812868,"threshold_uncertainty_score":0.01772887,"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."}}