{"id":"W2803358835","doi":"10.1016/j.meatsci.2018.05.012","title":"Predictability of lean product, bone, and fat trim in beef carcasses from Costa Rica","year":2018,"lang":"en","type":"article","venue":"Meat Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Animal science; Mathematics; Carcass weight; Trim; Body weight; Food science; Chemistry; Biology; Internal medicine; Medicine; Computer science","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":[0.0006791244,0.0002826882,0.0002235947,0.0009129751,0.0003676271,0.0006717873,0.0003102947,0.0003070257,0.0007131246],"category_scores_gemma":[0.001277208,0.000176537,0.0003068706,0.001062314,0.0004519758,0.0001819787,0.0005202293,0.0001785064,0.0001847726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009419619,"about_ca_system_score_gemma":0.0003234562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1541012,"about_ca_topic_score_gemma":0.2422571,"domain_scores_codex":[0.9997244,0.00009635935,0.00001641765,0.00007518715,0.00003347348,0.00005400715],"domain_scores_gemma":[0.999275,0.0001815278,0.0002285594,0.0001106546,0.0001508798,0.00005327052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008626921,0.00001104612,0.9945904,0.000009345426,0.0001193986,0.00004675067,0.0002331847,0.0004809028,0.001869081,0.00004734643,0.00009270476,0.002413536],"study_design_scores_gemma":[6.76814e-7,0.000003642563,0.9994264,0.000002571093,0.000007487594,0.00001384646,0.0001200204,0.000308731,0.00004376224,0.000009519657,0.00006267564,8.126245e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991591,0.0001147967,0.00007489716,0.00002291017,9.541853e-7,0.000002506642,0.0002014241,0.000003439094,0.0004199365],"genre_scores_gemma":[0.9993962,0.00005379847,0.00006510212,0.00001434603,0.00000148101,0.000002433453,0.0002966709,0.000003936748,0.0001660304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1541012,"threshold_uncertainty_score":0.3064085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04461724868512404,"score_gpt":0.2699981683265827,"score_spread":0.2253809196414586,"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."}}