{"id":"W2886974613","doi":"10.1016/j.foodchem.2018.08.075","title":"Evaluation of near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy techniques combined with chemometrics for the determination of crude protein and intestinal protein digestibility of wheat","year":2018,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Agricultural Development Fund; Saskatchewan Forage Network","keywords":"Chemometrics; Near-infrared spectroscopy; Spectroscopy; Infrared spectroscopy; Chemistry; Fourier transform; Fourier transform infrared spectroscopy; Infrared; Analytical Chemistry (journal); Attenuated total reflection; Biological system; Chromatography; Mathematics; Optics; Organic chemistry; Biology","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":[0.0008303403,0.0002869164,0.0005035045,0.00009391324,0.0001250498,0.00003481812,0.0002676554,0.0002267413,0.000144326],"category_scores_gemma":[0.001202774,0.0002233138,0.00009490592,0.0007221083,0.0008261604,0.0001295908,0.00005626551,0.0001997585,7.628201e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000124723,"about_ca_system_score_gemma":0.0002739583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000295905,"about_ca_topic_score_gemma":0.000009969833,"domain_scores_codex":[0.9979728,0.00002270797,0.0005960805,0.0004161797,0.0007321633,0.0002600972],"domain_scores_gemma":[0.9974487,0.000230117,0.0005541233,0.0005239425,0.001162224,0.0000808425],"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":[0.0007884073,0.000216601,0.0011052,0.001652077,0.0001335355,2.15276e-7,0.0002382071,2.39839e-7,0.9906825,0.000007347577,0.00001554928,0.005160105],"study_design_scores_gemma":[0.001721476,0.001284325,0.0003294527,0.000289066,0.0006602877,0.0000101432,0.0003132978,0.001338147,0.9916002,0.002202236,0.00002919052,0.0002222124],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911048,0.0004547334,0.00447867,0.00008763049,0.000006365452,0.001016822,0.00008778404,0.00004642169,0.002716785],"genre_scores_gemma":[0.9767245,0.00001154782,0.02258273,0.000003494458,0.00005692905,0.0002977758,0.00003092865,0.00002954203,0.0002625385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01810406,"threshold_uncertainty_score":0.9106473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0217754907222684,"score_gpt":0.2855816526281865,"score_spread":0.263806161905918,"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."}}