Food Thermal Labels are a Source of Dietary Exposure to Bisphenol S and Other Color Developers
Bibliographic record
Abstract
To test the hypothesis that migration from the thermal labels on plastic film packaging is a major source of exposure to bisphenols and alternative color developers in food, we analyzed 140 packaging materials from packaged fresh food purchased in North America. No bisphenol A (BPA) was detected in either the packaging samples or thermal labels. However, significant amounts of bisphenol S (BPS) and alternative color developers (up to 214 μg/cm 2 ) were present in thermal labels; their relative occurrence varied among stores. In a controlled experiment, we wrapped fish in film with a thermal label for 5 days at 4 °C. The fish in contact with the label contained BPS (≤1140 ng/g wet weight [ww]), 4-hydroxyphenyl 4-isoprooxyphenylsulfone (D-8) (≤230 ng/g ww), bis(2-chloroethyl)ether-4,4’-dihydroxydiphenyl sulfone monomer (D-90) (≤3.41 ng/g ww), and/or Pergafast-201 (≤1.87 ng/g ww). The corresponding film samples were then tested using migration cells for 10 days; significantly higher BPS migration was observed systematically from the films with thermal labels compared to plain films. This study provides evidence, for the first time, that BPS and alternative thermal label color developers migrate from packaging materials into food. Further, BPS migration significantly exceeded the European Union Specific Migration Limit (50 ng/g ww), suggesting that further risk assessment studies are warranted.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".