{"id":"W2014693798","doi":"10.2527/jas.2006-694","title":"Genetic evaluation of beef carcass data using different endpoint adjustments","year":2007,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Animal science; Biology; Food science; Biotechnology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006952133,0.0005246454,0.0003048018,0.001196283,0.0001703165,0.0005569739,0.0002877415,0.0002589239,0.0003859444],"category_scores_gemma":[0.01104987,0.0001564372,0.0006951569,0.0009740415,0.0002655666,0.0002505572,0.0004039757,0.0003033908,0.000107576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004095558,"about_ca_system_score_gemma":0.0001738399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001834931,"about_ca_topic_score_gemma":0.002842385,"domain_scores_codex":[0.9958503,0.002322417,0.0002495284,0.000794609,0.0006394832,0.0001436019],"domain_scores_gemma":[0.9917225,0.004642275,0.001475065,0.001059562,0.0008692516,0.0002312703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001555479,0.000208975,0.9242151,0.00003330243,0.0009434431,0.0002910154,0.0003555111,0.01397746,0.03457363,0.0002252201,0.00008924832,0.02353153],"study_design_scores_gemma":[0.00001493524,0.0005044466,0.9831604,0.000004274031,0.0001309027,0.0001174863,0.00004245114,0.01229141,0.003496778,0.00007517762,0.0001425859,0.00001906885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966314,0.00002225348,0.003028026,0.000003852966,0.000001911414,0.000009348792,0.0001624144,0.00002438861,0.0001162544],"genre_scores_gemma":[0.9964418,0.00001427498,0.002545271,0.000003381257,0.000002179222,0.00001123378,0.0008358896,0.00002050303,0.0001254429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006952133,"threshold_uncertainty_score":0.03676683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0868025500681988,"score_gpt":0.3621131607720925,"score_spread":0.2753106107038937,"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."}}