{"id":"W2943991194","doi":"10.1016/j.foodchem.2019.05.060","title":"Classification of cow milk using artificial neural network developed from the spectral data of single- and three-detector spectrophotometers","year":2019,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Detector; Artificial neural network; Pattern recognition (psychology); Artificial intelligence; Cow milk; Biological system; Chemistry; Computer science; Food science; Physics; Optics; Biology","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":[0.00046992,0.0003622515,0.0003441605,0.0006683411,0.0001832373,0.0004675451,0.0003513338,0.0004890027,0.0006559854],"category_scores_gemma":[0.0008898095,0.0001304867,0.0003893236,0.0004768964,0.0001088845,0.0003361388,0.0001814804,0.0002674173,0.0001965395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004275012,"about_ca_system_score_gemma":0.0003132997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003114219,"about_ca_topic_score_gemma":0.002853584,"domain_scores_codex":[0.9998568,0.00002300659,0.00001206623,0.00003883598,0.0000467527,0.00002248977],"domain_scores_gemma":[0.9996499,0.0001127827,0.00004076984,0.00001512294,0.0001680009,0.00001346754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001720528,0.0005213998,0.07696624,0.0004179054,0.0002429017,0.0003507754,0.0001621787,0.1689561,0.2053166,0.001096819,0.001984593,0.5422639],"study_design_scores_gemma":[0.000007747268,0.00007388517,0.0156046,0.000009448132,0.0000340537,0.00004123773,0.00003657811,0.9591866,0.02421166,0.0003121755,0.0004669804,0.00001513505],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8834516,0.0007541079,0.1131219,0.0001242114,0.0001345109,0.00003837657,0.0003340226,0.0006533004,0.001387927],"genre_scores_gemma":[0.9705337,0.0001808046,0.02774728,0.00002900949,0.00001704505,0.00002569701,0.0002920278,0.00001579428,0.001158695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003114219,"threshold_uncertainty_score":0.006192207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0920350037923193,"score_gpt":0.2833387620410171,"score_spread":0.1913037582486978,"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."}}