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Record W1997700713 · doi:10.1080/02652030802562946

An isotope dilution headspace method with gas chromatography–mass spectrometry for determination of propylene oxide in food

2009· article· en· W1997700713 on OpenAlex
Xu‐Liang Cao, Jeannette Corriveau

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFood Additives & Contaminants Part A · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsHealth Canada
Fundersnot available
KeywordsPropylene oxideChemistryIsotope dilutionDilutionChromatographyMass spectrometryRepeatabilityDetection limitGas chromatographyGas chromatography–mass spectrometryAnalytical Chemistry (journal)OxideOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

A method based on isotope dilution headspace and gas chromatography-mass spectrometry was developed for the determination of propylene oxide in foods. Optimum method sensitivity was achieved by the addition of NaCl in water at saturation and with the sample solution incubated at 90 degrees C. The method had good repeatability with relative standard deviations of 6.0, 7.6 and 2.2% at 5, 20 and 40 microg l(-1), respectively. The method was used to determine propylene oxide in 36 selected food composite samples from the 2007 Canadian total diet study. Propylene oxide was not detected in any samples analyzed with an average method detection limit of 0.5 ng g(-1). Hydrolysis of propylene oxide in water was observed as a first-order reaction with a half-life of 15 h at room temperature and less than 10 min at 90 degrees C. This confirms that it is very unlikely to find propylene oxide in foods as consumed due to its volatility and reaction with water.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.224
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.316
Teacher spread0.305 · 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