{"id":"W3132285094","doi":"10.1111/jbg.12540","title":"Estimation of economic value for efficiency and animal health and welfare traits, teat and udder structure, in Canadian Angus cattle","year":2021,"lang":"en","type":"article","venue":"Journal of Animal Breeding and Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Innovates; University of Alberta; University of Calgary","funders":"Alberta Innovates Bio Solutions","keywords":"Udder; Sire; Heritability; Selection (genetic algorithm); Best linear unbiased prediction; Estimation; Animal welfare; Welfare; Biology; Genetic correlation; Genetic gain; Statistics; Animal science; Genetic variation; Economics; Mathematics; Mastitis; Genetics; 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":[0.002655007,0.0002664385,0.00026423,0.001715517,0.000550757,0.0008872126,0.0004749604,0.0002332991,0.0004273948],"category_scores_gemma":[0.005487185,0.0001487607,0.0003559578,0.001445028,0.0005833938,0.0003471556,0.000382874,0.0003115756,0.0000612207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006823981,"about_ca_system_score_gemma":0.002401266,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5617518,"about_ca_topic_score_gemma":0.6849751,"domain_scores_codex":[0.9990055,0.0003329135,0.00003577976,0.0001345193,0.0003755554,0.0001157554],"domain_scores_gemma":[0.9982595,0.0007603132,0.0003124558,0.00009603005,0.0004433047,0.000128446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002972076,0.00005601386,0.9569762,0.00003387406,0.0001864958,0.00004962937,0.0002535479,0.01259824,0.002554339,0.0009311024,0.0001454098,0.0259179],"study_design_scores_gemma":[0.00000403779,0.00005166928,0.9853027,0.000008370686,0.00002713024,0.00004316438,0.0001551847,0.0132576,0.0006093238,0.0002334117,0.0002946351,0.00001284091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977015,0.0001347217,0.001508807,0.00002528323,0.000001041429,0.000007183422,0.0001941351,0.000004698964,0.0004226719],"genre_scores_gemma":[0.9962193,0.00009634963,0.002886795,0.00000760172,0.000001284701,0.000006796356,0.000414079,0.000002868907,0.0003648685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4382482,"threshold_uncertainty_score":0.8816582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055489349156896,"score_gpt":0.2603100053974815,"score_spread":0.2497551119059125,"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."}}