{"id":"W2758325521","doi":"10.1186/s12711-017-0347-9","title":"Multi-breed genomic prediction using Bayes R with sequence data and dropping variants with a small effect","year":2017,"lang":"en","type":"article","venue":"Genetics Selection Evolution","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alberta; Strategiske Forskningsråd","keywords":"Bayes' theorem; Biology; Imputation (statistics); Single-nucleotide polymorphism; Genetics; Bayesian probability; Statistics; Computational biology; Genotype; Mathematics; Gene; Missing data","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002063339,0.0002073638,0.00013771,0.00004775076,0.0006452178,0.0001013339,0.0003006471,0.0001538621,0.000002614224],"category_scores_gemma":[0.00004402329,0.000181035,0.00001634764,0.00005654606,0.0001941421,0.00001774146,0.0001817874,0.0001148525,0.000001167755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004661991,"about_ca_system_score_gemma":0.0001596642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001730166,"about_ca_topic_score_gemma":0.0004870784,"domain_scores_codex":[0.9987511,0.00008237129,0.0001578773,0.0006244883,0.000121767,0.000262416],"domain_scores_gemma":[0.9988767,0.000007840204,0.0001932153,0.0007246787,0.0001094811,0.00008809609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002815555,0.00003932218,0.199059,0.0000390744,0.000117881,6.122578e-7,0.0000448017,0.009203822,0.788534,0.00002607387,0.00002093377,0.002632891],"study_design_scores_gemma":[0.001768594,0.001841422,0.8916007,0.00006420039,0.0001913999,0.000267818,0.00002602718,0.08975419,0.01383574,0.00005143496,0.0002719335,0.000326564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5847567,0.0002874262,0.4145242,0.000009373586,0.00009930128,0.0002376557,0.00004082471,0.00001542304,0.00002902593],"genre_scores_gemma":[0.8404269,0.00004782181,0.1590525,0.00001175132,0.0002308378,0.00001179356,0.0001099151,0.0000287246,0.00007982893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7746983,"threshold_uncertainty_score":0.7382393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04113875926128045,"score_gpt":0.2665709802047679,"score_spread":0.2254322209434875,"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."}}