{"id":"W4252749326","doi":"10.2527/2006.843546x","title":"Genetic correlations between live yearling bull and steer carcass traits adjusted to different slaughter end points. 1. Carcass lean percentage1,2","year":2006,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"","keywords":"Marbled meat; Animal science; Lean meat; Biology; Lean tissue; Genetic correlation; Genetic variation; Body weight; Genetics; Endocrinology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002125072,0.0001418699,0.0001720921,0.00009197226,0.0001565094,0.00005815075,0.00028592,0.00007306124,0.00003524474],"category_scores_gemma":[0.00004334694,0.0001158395,0.00006672783,0.0001264072,0.0002322027,0.00001223765,0.0001161453,0.0001487913,0.000005483982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003282284,"about_ca_system_score_gemma":0.000111613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004251804,"about_ca_topic_score_gemma":0.0000410779,"domain_scores_codex":[0.9987795,0.00003268572,0.0003224353,0.0002652254,0.0003083426,0.0002917804],"domain_scores_gemma":[0.9993484,0.00002393976,0.0001383905,0.0001147684,0.0001525105,0.0002219603],"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":[0.0001099023,0.00008594999,0.1309174,0.00001256788,0.00003144544,0.00000615126,0.0008023285,0.0007398174,0.8617052,0.0005696924,0.0006602044,0.004359294],"study_design_scores_gemma":[0.0003303587,0.00114086,0.9863301,0.00002362273,0.00004397367,0.00008272095,0.0002372506,0.0000284519,0.01070011,0.000205295,0.0007286355,0.0001486505],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953822,0.0003951875,0.003390481,0.0002048402,0.0001343,0.0001198917,0.00001888993,0.000003207098,0.0003510379],"genre_scores_gemma":[0.986335,0.00001089431,0.01287455,0.00007007649,0.0005403515,0.000001205283,0.000002118686,0.00001154976,0.0001541917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8554127,"threshold_uncertainty_score":0.4723796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152885011983649,"score_gpt":0.2494720726783976,"score_spread":0.2341835714800327,"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."}}