{"id":"W2522654324","doi":"10.1186/s12711-016-0244-7","title":"Assessing accuracy of imputation using different SNP panel densities in a multi-breed sheep population","year":2016,"lang":"en","type":"article","venue":"Genetics Selection Evolution","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; BIO (Canada)","funders":"Beef + Lamb New Zealand; New Zealand Vice-Chancellors' Committee; AgResearch","keywords":"Imputation (statistics); Genomic selection; Biology; Purebred; Single-nucleotide polymorphism; Crossbreed; Statistics; SNP; Population; Genome-wide association study; Breed; Genetics; Genotype; Mathematics; Missing data; Gene; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.03352257,0.0005366686,0.001374159,0.001041738,0.0005991417,0.001874441,0.001498349,0.00162668,0.001150619],"category_scores_gemma":[0.04774921,0.0004650554,0.001612715,0.001256537,0.000648474,0.001501903,0.001501532,0.001678098,0.000519787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005369057,"about_ca_system_score_gemma":0.0004437421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002877206,"about_ca_topic_score_gemma":0.003100431,"domain_scores_codex":[0.9884921,0.0066059,0.0007595105,0.002584956,0.001174208,0.0003832819],"domain_scores_gemma":[0.951574,0.03472133,0.002517689,0.006748367,0.004059053,0.0003794514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002453824,0.0003632836,0.6928473,0.000310237,0.003738743,0.0004529087,0.0009917845,0.1781338,0.02029662,0.001776566,0.001574842,0.09706019],"study_design_scores_gemma":[0.0001449221,0.00120382,0.498205,0.0001491803,0.00120656,0.000699029,0.000435304,0.4753167,0.01552351,0.004281818,0.002634496,0.0001996047],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8544056,0.0008707549,0.1406541,0.0003116871,0.00005467803,0.00008504877,0.001704577,0.0006007733,0.001312715],"genre_scores_gemma":[0.9456847,0.0001721283,0.0503471,0.0001340571,0.00001576844,0.00008944821,0.002995163,0.00007430582,0.000487285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03352257,"threshold_uncertainty_score":0.1772864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05691169146420683,"score_gpt":0.3125427388676689,"score_spread":0.2556310474034621,"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."}}