{"id":"W2060317590","doi":"10.1016/j.meatsci.2014.09.105","title":"Using dual energy X-ray absorptiometry for a rapid, non-invasive carcass fat and lean predictions in beef carcass primals","year":2014,"lang":"en","type":"article","venue":"Meat Science","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Agriculture and Agri-Food Canada","funders":"","keywords":"Dual-energy X-ray absorptiometry; Dual energy; Lean tissue; Lean meat; Food science; Animal science; Medicine; Chemistry; Biology; Internal medicine; Body weight; Bone mineral","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":[0.001259936,0.0006364432,0.0003778735,0.0008120137,0.0002977645,0.000878129,0.000422059,0.0008835277,0.001092268],"category_scores_gemma":[0.001225659,0.0005634857,0.0002329148,0.0003970446,0.0004427031,0.0005557061,0.0004169509,0.0009068547,0.0004939888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002000056,"about_ca_system_score_gemma":0.0003105137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001034307,"about_ca_topic_score_gemma":0.001915642,"domain_scores_codex":[0.9995326,0.0001581917,0.00002606397,0.000143894,0.0001065195,0.00003270931],"domain_scores_gemma":[0.9994301,0.0002719983,0.00006529185,0.00005133293,0.0001406905,0.00004057286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004653166,0.0004116595,0.3595085,0.0002523185,0.0001218716,0.0004854797,0.0004103917,0.00134552,0.5245675,0.0003609587,0.0003752682,0.1075074],"study_design_scores_gemma":[0.0001866811,0.002420743,0.7262094,0.0001245485,0.0003914211,0.004214264,0.0007894645,0.03585365,0.2266854,0.0007805839,0.002268609,0.00007526936],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627895,0.001250739,0.03440086,0.00008227198,0.00004730867,0.0000529395,0.0001583593,0.0000935188,0.001124556],"genre_scores_gemma":[0.9574624,0.0006936131,0.03918615,0.0001332614,0.00003483243,0.00005157993,0.0001227817,0.00004796311,0.002267396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001259936,"threshold_uncertainty_score":0.006663263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04917008617031173,"score_gpt":0.31291909871281,"score_spread":0.2637490125424983,"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."}}