{"id":"W2945715204","doi":"10.221751/rmc2016.101","title":"Evaluation of Total Lean and Saleable Meat Yield Prediction Equations and Dual Energy X-Ray Absorptiometry for a Rapid, Non-Invasive Yield Prediction in Beef","year":2017,"lang":"en","type":"article","venue":"Meat and Muscle Biology","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Loin; Yield (engineering); Lean meat; Lean tissue; Animal science; Carcass weight; Dual energy; Dual-energy X-ray absorptiometry; Mathematics; Body weight; Biology; Bone mineral; Materials science; Metallurgy","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005412539,0.001016303,0.0004600412,0.0006437077,0.0001772968,0.0008823684,0.0006339756,0.0005178198,0.0007151708],"category_scores_gemma":[0.006692756,0.0004724897,0.0004242654,0.0004000257,0.0002029374,0.0006762433,0.0005370539,0.0006251122,0.0003234251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003767099,"about_ca_system_score_gemma":0.0005785713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003455057,"about_ca_topic_score_gemma":0.004583842,"domain_scores_codex":[0.9980572,0.0008492251,0.0001057191,0.0003535016,0.0005807219,0.00005351183],"domain_scores_gemma":[0.9974745,0.001477657,0.000353689,0.0001039407,0.000511485,0.00007874396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00265899,0.0009506234,0.7993217,0.0001987337,0.0004795101,0.0001589462,0.0002086783,0.02278345,0.04006841,0.000291897,0.0004711216,0.132408],"study_design_scores_gemma":[0.0002296965,0.004558529,0.4468071,0.00006572375,0.0004586549,0.0004330485,0.0002665268,0.5191998,0.02670829,0.0002208913,0.0009850147,0.0000667294],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605815,0.0007863095,0.03729178,0.00008862769,0.00002203336,0.00009167942,0.0003547746,0.0001620079,0.0006214047],"genre_scores_gemma":[0.9554926,0.0003747756,0.04274711,0.00005173258,0.00001744246,0.00008234032,0.0004008409,0.00003088375,0.000802343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005412539,"threshold_uncertainty_score":0.02862453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09239158851800754,"score_gpt":0.2830373930306627,"score_spread":0.1906458045126551,"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."}}