Levels of bisphenol-A in different paper products in Guangzhou, China, and assessment of human exposure via dermal contact
Bibliographic record
Abstract
Bisphenol A (BPA) is a chemical widely used both in plastics production as a food and beverage container and in thermal papers as a color developer. Dietary consumption is the main route of human exposure to BPA, but dermal absorption through handling different papers might be underestimated or ignored. In this study, BPA in different paper products, including different types of papers, receipts and Chinese currencies, were investigated. BPA was detected in receipts (n = 87) and Chinese currencies (n = 46) with concentrations of 0.17-2.675 × 10(4) μg per g paper and 0.09-288.55 μg per g paper, respectively. Except for parchment papers (n = 3), copy papers (n = 3) and food contact papers (n = 3), BPA was measured in all of the other paper products, with levels of 0.01-6.67 μg per g paper. BPA transferred from thermal papers to common papers increased with the increasing contact pressure. Compared with that in water, the migration speed of BPA was doubled in the synthetic sweat. Washing hands could reduce BPA dermal exposure, and washing hands with lotion was the most efficient way. However, about 19-47% of BPA was still found on hands after different washing methods. Dermal absorption via handling of receipts and papers was estimated to be 36.45 ng per day for the general population and 1.54 × 10(-3) to 248.73 μg per day for a cashier. These values are below the maximum doses recommended by the U.S. Environmental Protection Agency and the European Food Safety Authority. However, due to its uncertain adverse effects on human beings, long-term BPA exposure through dermal absorption should be paid more attention, particularly for some occupational populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".