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Record W2435434361 · doi:10.5650/jos.ess16021

Collaborative Study of an Indirect Enzymatic Method for the Simultaneous Analysis of 3-MCPD, 2-MCPD, and Glycidyl Esters in Edible Oils

2016· article· en· W2435434361 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Oleo Science · 2016
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsOxford Frozen Foods (Canada)
Fundersnot available
KeywordsChemistryFood scienceChromatographyEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

A collaborative study was conducted to evaluate an indirect enzymatic method for the analysis of fatty acid esters of 3-monochloro-1,2-propanediol (3-MCPD), 2-monochloro-1,3-propanediol (2-MCPD), and glycidol (Gly) in edible oils and fats. The method is characterized by the use of Candida rugosa lipase, which hydrolyzes the esters at room temperature in 30 min. Hydrolysis and bromination steps convert esters of 3-MCPD, 2-MCPD, and glycidol to free 3-MCPD, 2-MCPD, and 3-monobromo-1,2-propanediol, respectively, which are then derivatized with phenylboronic acid, and analyzed by gas chromatography-mass spectrometry. In a collaborative study involving 13 laboratories, liquid palm, solid palm, rapeseed, and rice bran oils spiked with 0.5-4.4 mg/kg of esters of 3-MCPD, 2-MCPD, and Gly were analyzed in duplicate. The repeatability (RSDr) were < 5% for five liquid oil samples and 8% for a solid oil sample. The reproducibility (RSDR) ranged from 5% to 18% for all oil samples. These RSDR values were considered satisfactory because the Horwitz ratios were ≤ 1.3% for all three analytes in all oil samples. This method is applicable to the quantification of 3-MCPD, 2-MCPD, and Gly esters in edible oils.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.319
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it