{"id":"W2058715538","doi":"10.1016/j.meatsci.2015.07.006","title":"Rapid discrimination of enhanced quality pork by visible and near infrared spectroscopy","year":2015,"lang":"en","type":"article","venue":"Meat Science","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Agriculture and Agri-Food Canada","funders":"Alberta Livestock and Meat Agency; Alberta Crop Industry Development Fund","keywords":"Breed; Moisture; Near-infrared spectroscopy; Partial least squares regression; Food science; Animal science; Chemistry; Biology; Mathematics","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":[0.00151075,0.00008472281,0.000149402,0.000009004677,0.0002033992,0.00009144799,0.0002603128,0.00003081857,0.00007473587],"category_scores_gemma":[0.0004249865,0.00003353817,0.00002326932,0.0005380608,0.0005626464,0.0003663039,0.00008757252,0.00005336925,0.000008313929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001896207,"about_ca_system_score_gemma":0.00002941386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002938092,"about_ca_topic_score_gemma":0.00005093583,"domain_scores_codex":[0.9986978,0.00007924195,0.0002086934,0.0003415255,0.0004548744,0.0002179149],"domain_scores_gemma":[0.9994689,0.00005282404,0.000100918,0.00007607225,0.0001479558,0.0001533609],"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":[0.00002290342,0.0000388854,0.002090221,0.000006230253,6.879122e-7,8.365095e-8,0.0003455895,1.894203e-7,0.9880209,0.0007080898,0.000555041,0.008211165],"study_design_scores_gemma":[0.0001146641,0.0003229487,0.1020729,0.00001110422,0.000002874958,6.474846e-7,0.0006471206,0.00004166942,0.8917642,0.002759763,0.002140881,0.0001213287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917853,0.0002539469,0.00003528372,0.0006941871,0.00008192882,0.0001064867,0.00001450079,0.00002557898,0.007002714],"genre_scores_gemma":[0.9988806,0.00002547987,0.0005635592,0.00008568337,0.0000480443,0.000002121662,0.00000896215,3.643694e-7,0.0003851349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09998263,"threshold_uncertainty_score":0.2073094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06375413084333278,"score_gpt":0.3059850180145006,"score_spread":0.2422308871711678,"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."}}