Survey of formaldehyde, acetaldehyde and oligomers in polyethylene terephthalate food-packaging materials Part A Chemistry, analysis, control, exposure & risk assessment
Bibliographic record
Abstract
Polyethylene terephthalate (PET) is frequently used as a packaging material for beverage bottles, fruit and vegetable trays, and egg crates in Japan. Levels of formaldehyde (FA), acetaldehyde (AA) and PET oligomers in various PET food packaging were determined. PET samples were initially dissolved in trifluoroacetic acid with 2,4-dinitrophenylhydrazine to derivatize formaldehyde and acetaldehyde to their dinitrophenylhydrazones. The stable derivatives along with the oligomers were analysed using HPLC with ultraviolet light detection at 360 and 254nm, respectively. The PET pellets contained 3.5-12.4μgg -1 AA and 4.0-7.2mgg -1 oligomers, while FA was below the determination limit. FA, AA and oligomer levels in Japanese bottles were 0.6-3.0μgg -1 , 8.4-25.7μgg -1 and 5.0-8.7mgg -1 , ND-1.6μgg -1 , 5.0-13.1μgg -1 and 4.9-8.2mgg -1 in French and Italian bottles, and ND-1.2μgg -1 , 9.1-18.7μgg -1 and 5.6-8.0mgg -1 in US and Canadian bottles, respectively. Compared with European bottles, Japanese bottles contain higher FA and AA levels. In sheet-moulding products, their contents were determined as ND-1.1μgg -1 , 11.5-43.1μgg -1 and 4.6-9.2mgg -1 , respectively. The results show that sheet-moulding products contain lower FA and higher AA in comparison with bottles. FA and AA are considered to be generated from PET during the heating process for moulding the pellets to bottles or sheet-moulding articles and de-aeration during the sheet-moulding process is effective in removing FA. In contrast, the level of the oligomers remains unchanged during the moulding process from pellets to bottles or sheet products.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".