{"id":"W2165194160","doi":"10.1186/1755-8794-5-12","title":"Evaluation of the imputation performance of the program IMPUTE in an admixed sample from Mexico City using several model designs","year":2012,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Banting and Best Diabetes Centre, University of Toronto; Instituto Mexicano del Seguro Social; Consejo Nacional de Ciencia y Tecnología; Canadian Institutes of Health Research; Ontario Innovation Trust","keywords":"Imputation (statistics); International HapMap Project; Missing data; Concordance; 1000 Genomes Project; Statistics; Genotype; Biology; Genetics; Genotyping; Mathematics; 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":[0.002157606,0.00007151913,0.0001237864,0.00001269741,0.00004830192,0.000002492509,0.0002139599,0.0001803986,0.000009041493],"category_scores_gemma":[0.001014417,0.00004783017,0.00006394638,0.00007255418,0.00008117946,0.000004962493,0.0001157278,0.00007834829,1.50262e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006016063,"about_ca_system_score_gemma":0.0007579885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001582363,"about_ca_topic_score_gemma":0.000420526,"domain_scores_codex":[0.9986194,0.0004877489,0.0003069507,0.0001257814,0.0002895657,0.0001705013],"domain_scores_gemma":[0.9992913,0.00006352656,0.000211809,0.0002478354,0.0001277893,0.00005775233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002518899,0.0001309656,0.7243099,0.000007771856,0.00002190365,4.141039e-9,0.0002542794,0.2435536,0.02268854,0.00001320202,0.0000148059,0.008979934],"study_design_scores_gemma":[0.0002646866,0.00003533194,0.3411032,0.000006215902,0.00003552234,4.995078e-7,0.0000275621,0.6539083,0.004256154,0.0003160593,0.000007744543,0.0000387847],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9450049,0.0001065836,0.05440142,0.00002966402,0.0001284445,0.00029832,0.00001965671,0.000001854957,0.000009188494],"genre_scores_gemma":[0.9668742,0.00002161501,0.03285867,0.00008012233,0.00009494344,0.00001599109,0.00004582734,0.000006690119,0.000001903733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4103547,"threshold_uncertainty_score":0.1950458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.116223278406938,"score_gpt":0.3578967278390289,"score_spread":0.2416734494320909,"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."}}