{"id":"W2970421370","doi":"10.3168/jds.2019-16821","title":"Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle","year":2019,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canadian Dairy Commission; Dairy Farmers of Canada","keywords":"SNP; Single-nucleotide polymorphism; Biology; Best linear unbiased prediction; Quantitative trait locus; Genetics; Genome-wide association study; Dairy cattle; Trait; Candidate gene; Regression; Selection (genetic algorithm); Statistics; Gene; Genotype; Mathematics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001602689,0.0003281601,0.0004309642,0.001111642,0.00133421,0.0006540758,0.0008350568,0.0004057689,0.00118964],"category_scores_gemma":[0.001957341,0.0001826351,0.000744312,0.001710489,0.000541041,0.0001483653,0.000445735,0.0004794899,0.0001003061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004477121,"about_ca_system_score_gemma":0.005083038,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8909694,"about_ca_topic_score_gemma":0.9508212,"domain_scores_codex":[0.9989603,0.0001553992,0.00004323759,0.0004073746,0.000217514,0.0002162125],"domain_scores_gemma":[0.9984189,0.0004195024,0.0002736587,0.0001609412,0.0004523312,0.0002746887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003043144,0.00002229035,0.9852622,0.0000247643,0.0004940283,0.0001163702,0.0003436348,0.0005716527,0.004487033,0.0001378468,0.0004473002,0.007788599],"study_design_scores_gemma":[0.000003983605,0.000009960479,0.9988701,0.000003884636,0.00005792472,0.00002298367,0.00008024094,0.00059185,0.00006351735,0.00001041133,0.0002805073,0.000004658785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970978,0.0004411945,0.000596211,0.00006110733,0.000007006334,0.000009427785,0.001247439,0.00001834495,0.0005213597],"genre_scores_gemma":[0.9961538,0.0001628343,0.001428502,0.0000398329,0.000004490934,0.00002085417,0.001554639,0.0000110335,0.0006239789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1090306,"threshold_uncertainty_score":0.2193454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01737558956017601,"score_gpt":0.2345993815672323,"score_spread":0.2172237920070562,"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."}}