Bisphénol A et substituts du BPA dans certains aliments en conserve et aliments en pot pour nourrissons : 1er avril 2023 au 31 mars 2024
Bibliographic record
Abstract
Bisphenol A (BPA) is a chemical used to make Bisphenol A diglycidyl ether (BADGE) epoxy resins and hard plastic containers. Its use in the food industry is common, as BADGE epoxy resins are often coated on the inside of cans to prevent direct contact between the food and the metal. These compounds can migrate into food, particularly at elevated temperatures (for example, in hot-filled or heat-processed canned foods). To prevent the adverse health effects of these componds, some manufacturers have turned to BPA alternatives such as Bisphenol F (BPF) and Bisphenol S (BPS). Limited data is available concerning the use of BPA alternatives in canned and bottled foods, therefore they were included in this survey. A total of 353 samples were collected from retail stores in 11 cities across Canada. The samples collected included coconut milk, infant formula, ready-to-eat (RTE) curry products, meat, pasta, soup, and jarred infant food. BPA was detected in 33% of the survey samples and other analogues were detected in 8%. No samples had detected levels of BPS. The highest average and maximum BPA levels were reported in canned food samples and the lowest in infant foods. The results from this survey were comparable to those found in previous surveys. Maximum Levels (MLs) for BPA, BADGE, BPF and BPS have not been established, so levels were assessed by Health Canada on a case-by-case basis using the most current scientific data. The levels observed in this survey were evaluated by Health Canada who determined that none of the samples would pose an unacceptable human health concern, therefore there were no recalls resulting from this survey.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".