Di-(2-ethylhexyl) adipate and 20 phthalates in composite food samples from the 2013 Canadian Total Diet Study
Bibliographic record
Abstract
A sensitive and selective GC-MS method was developed and used for simultaneous analysis of di-(2-ethylhexyl) adipate (DEHA) and 20 selected phthalates in the food samples from the 2013 Canadian Total Diet Study. At least one of the 21 target chemicals was detected in 141 of the 159 different food composite samples analysed. However, only seven of the 21 target chemicals were detected, with di-(2-ethylhexyl) phthalate (DEHP) and DEHA being detected most frequently, in 111 and 91 different food composite samples, respectively, followed by di-n-butyl phthalate (DBP) (n = 44), n-butyl benzyl phthalate (BBzP) (32), di-iso-butyl phthalate (DiBP) (27), di-ethyl phthalate (DEP) (3), and di-cyclohexyl phthalate (DCHP) (1). Levels of DEP (di-ethyl phthalate), DiBP, DBP, BBzP and DCHP were low, in general, with average concentrations of 9.63, 8.26, 23.2, 12.4 and 64.9 ng g(-1), respectively. Levels of DEHA and DEHP varied widely, ranging from 1.4 to 6010 ng g(-1) and from 14.4 to 714 ng g(-1), respectively. High levels of DEHA were found mainly in the composite samples where the individual food items used to prepare the composite were likely packaged in polyvinyl chloride (PVC) wrapping film, while the highest DEHP levels were found in the vegetable and fruit samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".