{"id":"W2891205235","doi":"10.1016/j.heliyon.2018.e00806","title":"Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants","year":2018,"lang":"en","type":"article","venue":"Heliyon","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Oak Ridge Institute for Science and Education; U.S. Food and Drug Administration; University of Maryland; Advanced Research Projects Agency - Energy; Canadian Food Inspection Agency; U.S. Department of Energy","keywords":"Adulterant; Near-infrared spectroscopy; Chemometrics; Spectrometer; Spectroscopy; Chromatography; Analytical Chemistry (journal); Materials science; Chemistry; Optics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002285675,0.0001513352,0.0001322899,0.00007745859,0.0003420396,0.00008535199,0.0001565603,0.000120441,0.00004101212],"category_scores_gemma":[0.00005050468,0.0001588368,0.00005690204,0.0001162576,0.0001194859,0.00001173406,0.00004427688,0.0000559999,0.00003290235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001903603,"about_ca_system_score_gemma":0.0000568529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007714469,"about_ca_topic_score_gemma":0.00003608488,"domain_scores_codex":[0.9987891,0.00006353177,0.0003198485,0.0004724698,0.0001438719,0.0002112016],"domain_scores_gemma":[0.9989638,0.000007716776,0.0001607329,0.000429223,0.000366652,0.00007186722],"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":[0.0002056594,0.0002570735,0.002495428,0.00003886551,0.00004766567,1.664538e-7,0.0004562368,0.000001039715,0.9952432,0.00008866295,0.0006858428,0.0004801917],"study_design_scores_gemma":[0.002410873,0.0008463333,0.1718718,0.00004401973,0.0001295765,0.00001192255,0.001048451,0.003320532,0.812199,0.00004953751,0.007661059,0.000406908],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799643,0.0001596114,0.01804671,0.0002916685,0.0005077411,0.0008744163,0.00004060023,0.00002126672,0.00009374732],"genre_scores_gemma":[0.9966866,0.00005463458,0.00165261,0.0001648332,0.0006471562,0.00008266015,0.000264278,0.00002894892,0.0004182255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1830442,"threshold_uncertainty_score":0.6477175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03286801191065341,"score_gpt":0.3262302598513713,"score_spread":0.2933622479407179,"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."}}