{"id":"W2590121248","doi":"10.1007/s40362-017-0041-x","title":"Genotype Imputation Methods and Their Effects on Genomic Predictions in Cattle","year":2016,"lang":"en","type":"article","venue":"Springer Science Reviews","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Livestock and Meat Agency; Western Canada Research Grid; Compute Canada; Genome Canada","keywords":"Imputation (statistics); Minor allele frequency; Statistics; Purebred; Genomic selection; Genotype; Concordance; Genotyping; Crossbreed; Biology; Single-nucleotide polymorphism; Missing data; Mathematics; Genetics; 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":[0.02487287,0.0009693968,0.001427075,0.001275389,0.0004214793,0.001749525,0.001377054,0.001055663,0.001600574],"category_scores_gemma":[0.06302631,0.0006872621,0.001602206,0.002306822,0.0004909924,0.00128658,0.000850127,0.001850969,0.0006891913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004839148,"about_ca_system_score_gemma":0.0006998956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003369511,"about_ca_topic_score_gemma":0.002636957,"domain_scores_codex":[0.9829705,0.01397698,0.0004477141,0.001238041,0.001224826,0.0001418967],"domain_scores_gemma":[0.9414296,0.05190726,0.001818832,0.002291148,0.002405055,0.0001481085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001121764,0.00009865146,0.05225221,0.0008794487,0.002369568,0.0001999376,0.0003494084,0.3641728,0.003475515,0.007086285,0.006363476,0.5616308],"study_design_scores_gemma":[0.0001629949,0.0003200609,0.02603309,0.0005836092,0.0007356291,0.0006173502,0.00009668159,0.9289864,0.007464607,0.02082609,0.01400828,0.0001652744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06072289,0.01716922,0.9148363,0.001309445,0.0002112271,0.00006651418,0.001358576,0.002160595,0.002165248],"genre_scores_gemma":[0.3665566,0.008365634,0.6185675,0.0007414616,0.0002472758,0.0002004216,0.003129198,0.0008236239,0.00136827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02487287,"threshold_uncertainty_score":0.1315418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784214761161648,"score_gpt":0.3137637288144987,"score_spread":0.2959215812028822,"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."}}