{"id":"W3048947060","doi":"10.1007/s12393-020-09246-9","title":"Assessment of Intramuscular Fat Quality in Pork Using Hyperspectral Imaging","year":2020,"lang":"en","type":"article","venue":"Food Engineering Reviews","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; McGill University","funders":"","keywords":"Intramuscular fat; Loin; Hyperspectral imaging; Partial least squares regression; Polyunsaturated fatty acid; Food science; Fatty acid; Coefficient of determination; Mathematics; Chemistry; Artificial intelligence; Computer science; Statistics; Biochemistry","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":[0.0005224523,0.0004450949,0.0002426508,0.0004713246,0.00008345664,0.0004611608,0.0002152133,0.0003906811,0.0005274643],"category_scores_gemma":[0.0002704596,0.0001444834,0.0002477043,0.0003177677,0.000287478,0.0004130032,0.0002502805,0.0004684324,0.0001600094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002323594,"about_ca_system_score_gemma":0.00009740402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008784897,"about_ca_topic_score_gemma":0.001810743,"domain_scores_codex":[0.9997976,0.00002962998,0.000006236839,0.00004193999,0.0001055178,0.00001911969],"domain_scores_gemma":[0.9997848,0.00004227907,0.0000587516,0.000008610273,0.00009447192,0.00001106397],"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":[0.0001944201,0.00004284729,0.003852915,0.0004682578,0.00008031155,0.00004517736,0.00006219707,0.0004690366,0.8967319,0.0001370969,0.0003339043,0.09758192],"study_design_scores_gemma":[0.00001226501,0.001002644,0.1192485,0.0001726626,0.0002145227,0.000957736,0.0004339793,0.008726637,0.8584457,0.0005933784,0.0101289,0.00006308073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8215989,0.08772095,0.07938854,0.0009468013,0.0002760166,0.00005591522,0.0003143558,0.000200928,0.009497509],"genre_scores_gemma":[0.8685975,0.06628773,0.05343545,0.0005632509,0.000202265,0.00004098286,0.0004958073,0.00005798147,0.01031911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008784897,"threshold_uncertainty_score":0.002763033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09676615771462437,"score_gpt":0.3085947447311734,"score_spread":0.211828587016549,"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."}}