{"id":"W6998675621","doi":"","title":"Analysis of edible oils by Fourier transform near-infrared spectroscopy","year":2000,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Edible Oils Quality and Analysis","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Analytical Chemistry (journal); Peroxide value; Partial least squares regression; Chemometrics; Fourier transform; Spectroscopy; Sample preparation; Acid value","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0009347424,0.001250531,0.00259024,0.0009547242,0.001061473,0.0001961566,0.001294099,0.002012826,0.02242655],"category_scores_gemma":[0.0003105323,0.001386016,0.002506336,0.003422528,0.00017001,0.0007418092,0.00004950895,0.002345452,0.0001903295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005925025,"about_ca_system_score_gemma":0.000158979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001129992,"about_ca_topic_score_gemma":0.00230307,"domain_scores_codex":[0.992842,0.000207841,0.002195745,0.001684079,0.001878666,0.001191678],"domain_scores_gemma":[0.9957444,0.000364013,0.001156234,0.001690912,0.0004467251,0.0005976962],"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":[0.00174991,0.001513986,0.0001870993,0.006065365,0.02161615,0.0001018613,0.0001315126,0.0002894235,0.854806,0.003212955,0.0002908849,0.1100349],"study_design_scores_gemma":[0.001123245,0.00008449585,0.00003418594,0.000667916,0.0118817,0.000003233421,0.000612061,0.0003572923,0.9269694,0.004867446,0.05176076,0.001638252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6444165,0.0009680334,8.902152e-7,0.00001392317,0.0002163136,0.0001412755,0.007901499,0.0002101784,0.3461314],"genre_scores_gemma":[0.6802613,0.0142563,0.004940938,0.0005229186,0.0003535435,0.0003887661,0.06111861,0.0009138377,0.2372438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1088876,"threshold_uncertainty_score":0.9999562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080373363405395,"score_gpt":0.2546383835787662,"score_spread":0.2438346499447123,"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."}}