{"id":"W3200099300","doi":"10.82308/43098","title":"Novel approaches to automated quality control analyses of edible oils by Fourier transform infrared spectroscopy : determination of free fatty acid and moisture content","year":2005,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Sultan Qaboos University","keywords":"Water content; Fourier transform infrared spectroscopy; Moisture; Food science; Chemistry; Infrared spectroscopy; Fourier transform; Fatty acid; Analytical Chemistry (journal); Quality (philosophy); Infrared; Content (measure theory); Spectroscopy; Environmental science; Chromatography; Mathematics; Biochemistry; Engineering; Chemical engineering; Organic chemistry; Optics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003142636,0.001526044,0.0008580855,0.002393523,0.0004232723,0.001835407,0.00222258,0.001217999,0.0009660798],"category_scores_gemma":[0.003219897,0.0008482384,0.0007417554,0.001493465,0.0009939465,0.001752205,0.00131057,0.001909402,0.0006437908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008910126,"about_ca_system_score_gemma":0.0008558024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254778,"about_ca_topic_score_gemma":0.002258507,"domain_scores_codex":[0.9960983,0.0003684957,0.0001749791,0.000893792,0.002339264,0.0001251647],"domain_scores_gemma":[0.9976128,0.0004754442,0.0004683448,0.000301342,0.001068516,0.00007357043],"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":[0.0001114809,0.00009359307,0.0008235555,0.0002320035,0.00005349388,0.00006612949,0.00008753117,0.0006590163,0.9523466,0.0007128638,0.000161944,0.04465171],"study_design_scores_gemma":[0.00003513811,0.0002763874,0.00318052,0.000040493,0.00006248849,0.0003669446,0.00005337848,0.02241906,0.9676747,0.0006859599,0.005132443,0.0000723854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06594241,0.002353678,0.9279341,0.0001591061,0.0001605713,0.0002880471,0.000374379,0.001670871,0.001116954],"genre_scores_gemma":[0.1445931,0.002760987,0.848371,0.0002451347,0.0001257571,0.0004712327,0.0006978236,0.000243367,0.002491553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003142636,"threshold_uncertainty_score":0.01662004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08116416978863486,"score_gpt":0.2995500878979738,"score_spread":0.2183859181093389,"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."}}