Trends of bisphenol A occurrence in canned food products from 2008–2020
Bibliographic record
Abstract
It is known that the industry already abandoned the use of bisphenol A (BPA)-based epoxy resins as internal coatings for some canned food products (e.g. infant formula, soups). The presence of bisphenol A (BPA) in foods has also been extensively investigated, especially since late 2000. However, information on temporal trends of BPA occurrence in foods is very limited. It is not clear if BPA-based epoxy resins are still being used in internal coating for many other canned foods and if the overall exposure to BPA through consumption of canned foods has significantly decreased. As part of the Canadian total diet study (TDS) program, we have been analysing food samples for BPA since 2008. In this study, results of BPA in samples of different composite canned foods from 2008-2020 TDS were reported. Clear temporal trends were observed for canned fish and soups, with BPA levels being significantly reduced since 2014 for canned fish products and 2017 for canned soups. Temporal trends were not observed for canned evaporated milk, luncheon meats, and vegetables, with even the highest levels of BPA being detected in recent samples for evaporated milk (57 ng/g), luncheon meats (56 ng/g), and baked beans (103 ng/g). This seems to indicate that BPA-based epoxy resins are still being used in the internal coatings for these canned foods products. Thus, analysis of canned food samples for BPA should be continued for exposure assessment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".