Survey of formaldehyde, acetaldehyde and oligomers in polyethylene terephthalate food-packaging materials
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
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 254 nm, respectively. The PET pellets contained 3.5-12.4 microg g-1 AA and 4.0-7.2 mg g-1 oligomers, while FA was below the determination limit. FA, AA and oligomer levels in Japanese bottles were 0.6-3.0 microg g-1, 8.4-25.7 microg g-1 and 5.0-8.7 mg g-1, ND-1.6 microg g-1, 5.0-13.1 microg g-1 and 4.9-8.2 mg g-1 in French and Italian bottles, and ND-1.2 microg g-1, 9.1-18.7 microg g-1 and 5.6-8.0 mg g-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-1.1 microg g-1, 11.5-43.1 microg g-1 and 4.6-9.2 mg g-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.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it