{"id":"W2036490200","doi":"10.1016/j.meatsci.2005.02.015","title":"The accuracy of predicting carcass composition of three different pig genetic lines by dual-energy X-ray absorptiometry","year":2005,"lang":"en","type":"article","venue":"Meat Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Loin; Dual energy; Carcass weight; Dual-energy X-ray absorptiometry; Lean tissue; Mathematics; Bone mineral content; Composition (language); Lean meat; Statistics; Animal science; Bone mineral; Body weight; Medicine; Biology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005479143,0.0001012213,0.0001483394,0.00001684398,0.0004022825,0.00005303329,0.0004609191,0.00003227443,0.00003229741],"category_scores_gemma":[0.0001789411,0.0000323871,0.00005719637,0.0006156994,0.0005143663,0.0001576715,0.0001228922,0.00006063139,0.000001913114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001738116,"about_ca_system_score_gemma":0.0000104475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00028655,"about_ca_topic_score_gemma":0.000271865,"domain_scores_codex":[0.9986174,0.00006064749,0.0003230452,0.0002757483,0.0004758328,0.0002472858],"domain_scores_gemma":[0.999153,0.0003158926,0.0001951322,0.0001055047,0.0001594314,0.00007100716],"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":[0.000009339984,0.00006258709,0.02292498,0.000005338002,0.000002555424,6.893743e-8,0.00003620407,0.00001513936,0.9316868,0.0004829454,0.00006820895,0.0447058],"study_design_scores_gemma":[0.00007639596,0.0002044935,0.4604322,0.00002307397,0.000009431814,0.000001746364,0.0000923382,0.001946149,0.5355947,0.0004910332,0.001015317,0.0001131237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977571,0.0006640168,0.0000896411,0.0009685776,0.00009633144,0.00008125885,0.00002562181,0.00001845259,0.0002990364],"genre_scores_gemma":[0.9994739,0.00007874956,0.0001216169,0.00004018415,0.0002142066,0.000003562659,0.000006368611,5.443678e-7,0.00006083417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4375072,"threshold_uncertainty_score":0.3094072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03161825851880201,"score_gpt":0.2545038772021596,"score_spread":0.2228856186833576,"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."}}