{"id":"W2783831679","doi":"10.1007/s13197-018-3033-1","title":"Non-destructive and rapid evaluation of aflatoxins in brown rice by using near-infrared and mid-infrared spectroscopic techniques","year":2018,"lang":"en","type":"article","venue":"Journal of Food Science and Technology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; National Natural Science Foundation of China","keywords":"Infrared; Aflatoxin; Infrared Spectrophotometry; Infrared spectroscopy; Brown rice; Environmental science; Materials science; Environmental chemistry; Chemistry; Food science; Optics; Physics; Chromatography; Organic chemistry","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":[0.000456213,0.0003392712,0.000206132,0.0004331197,0.0002440545,0.0002631138,0.0002517502,0.0003136203,0.0003823183],"category_scores_gemma":[0.0003223179,0.0001944477,0.0002179547,0.0002555894,0.0003104616,0.0004258592,0.0002627388,0.0004634325,0.0002574948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001326633,"about_ca_system_score_gemma":0.000292145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009071066,"about_ca_topic_score_gemma":0.001880086,"domain_scores_codex":[0.9996638,0.00005805258,0.00001583457,0.00007584514,0.0001543347,0.00003209348],"domain_scores_gemma":[0.9997388,0.000069059,0.00004550378,0.00002374184,0.0001004804,0.00002244345],"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":[0.0001186192,0.00001567487,0.000799865,0.00003099472,0.000004832588,0.00001567172,0.00002007849,0.00004173187,0.9952765,0.00002891595,0.00001621973,0.003630852],"study_design_scores_gemma":[0.00001122066,0.0002772595,0.01741648,0.000005500502,0.00003552355,0.0003100522,0.0000898772,0.001976501,0.9789491,0.000101736,0.0008128591,0.00001397414],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9506961,0.001937093,0.04471168,0.00008227932,0.00003417182,0.00004741977,0.0002398946,0.0001692579,0.002082122],"genre_scores_gemma":[0.938098,0.001242172,0.05573706,0.0001043563,0.00002592517,0.00007090622,0.0002850471,0.00003196676,0.004404574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009071066,"threshold_uncertainty_score":0.002412736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02036086527721531,"score_gpt":0.3091618437986005,"score_spread":0.2888009785213851,"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."}}