Di-(2-ethylhexyl) adipate and 20 phthalates in composite food samples from the 2013 Canadian Total Diet Study
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.
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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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it