{"id":"W4390883198","doi":"10.1093/bib/bbad509","title":"Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels","year":2023,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Institute of Genetics","funders":"Alliance de recherche numérique du Canada; Ministry of Education, Culture, Sports, Science and Technology; University of Tokyo; Japan Agency for Medical Research and Development","keywords":"Imputation (statistics); Statistics; Econometrics; Standard deviation; Mathematics; Biology; Computer science; Missing data","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":[0.00128112,0.00009277145,0.0001881292,0.00005748442,0.00006019468,0.0000134616,0.0002151464,0.0001603915,0.000001099482],"category_scores_gemma":[0.002878323,0.00006000217,0.00004059621,0.0004803144,0.0001820116,0.000008567033,0.0001762686,0.0001345776,0.000002449454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001470215,"about_ca_system_score_gemma":0.0000762317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000456836,"about_ca_topic_score_gemma":0.0001751058,"domain_scores_codex":[0.9988752,0.0001332933,0.0005749719,0.0001163237,0.0001093883,0.0001908031],"domain_scores_gemma":[0.9989901,0.0002989445,0.0003868868,0.000240948,0.00006384314,0.0000192757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001486574,0.0001014615,0.9339418,0.0004082122,0.00007178748,9.927261e-7,0.005062599,0.006676861,0.006045937,0.001956204,0.001549407,0.04403608],"study_design_scores_gemma":[0.001130396,0.00002329681,0.9785749,0.00002313914,0.000008123616,0.000003192787,0.0008341876,0.01675569,0.001014617,0.0006952349,0.0008311483,0.0001060532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971488,0.0002740161,0.001242083,0.0008163451,0.00006745147,0.0002184654,0.00002270277,0.000005454947,0.0002046914],"genre_scores_gemma":[0.9937397,0.0009834351,0.004552249,0.0005824807,0.00001390886,0.00001763134,0.00003738684,0.000005008415,0.00006820057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04463312,"threshold_uncertainty_score":0.3445829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09631303735923048,"score_gpt":0.3610884832077939,"score_spread":0.2647754458485634,"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."}}