{"id":"W2910262093","doi":"10.1017/s1751731118003348","title":"Estimation of genetic parameters for BW and body measurements in Brahman cattle","year":2019,"lang":"en","type":"article","venue":"animal","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"AGE-WELL","keywords":"Heritability; Brahman; Restricted maximum likelihood; Animal science; Genetic correlation; Biology; Herd; Beef cattle; Multivariate statistics; Body weight; Variance components; Animal breeding; Veterinary medicine; Genetic variation; Statistics; Maximum likelihood; Breed; Mathematics; Genetics; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001413676,0.0003719766,0.0003201194,0.0009747113,0.0002328699,0.0004738674,0.000259645,0.0002140877,0.0006953358],"category_scores_gemma":[0.00194325,0.0002717423,0.0004953374,0.001022387,0.0003260532,0.0001919577,0.000247083,0.0004187001,0.0001295393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004189476,"about_ca_system_score_gemma":0.0002822729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009750726,"about_ca_topic_score_gemma":0.01503748,"domain_scores_codex":[0.9992545,0.0003067901,0.0000416579,0.0001867898,0.0001403035,0.00006987658],"domain_scores_gemma":[0.9985867,0.0008101462,0.0003158606,0.0001162786,0.0001093084,0.00006179444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004516202,0.0001148288,0.9315367,0.0000616683,0.0004297328,0.0004201151,0.000891536,0.007591641,0.02358311,0.0002431935,0.00007183276,0.03460399],"study_design_scores_gemma":[0.000006776432,0.00007244239,0.9927346,0.00001419076,0.00005375981,0.0001527016,0.0001445365,0.005994436,0.0006070735,0.00008226181,0.000126214,0.00001109354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974293,0.00008514012,0.002204039,0.000005827128,0.000001368163,0.00000493273,0.0001178816,0.000008181152,0.0001432386],"genre_scores_gemma":[0.9968628,0.00007398614,0.002348444,0.000002457433,0.000002527736,0.00001082614,0.0004997869,0.000008098559,0.0001910747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009750726,"threshold_uncertainty_score":0.01938796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814713481945663,"score_gpt":0.2561385566926899,"score_spread":0.2379914218732333,"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."}}