Can bisphenol‐A migrating from canned food contribute to the obesity epidemic? (959.10)
Bibliographic record
Abstract
The prevalence of obesity has increased dramatically in the last two decades. Several studies suggest a link between Bisphenol‐A (BPA) exposure and obesity. Although BPA is banned now in baby bottles, in recent years there has been increasing public awareness and concern about the possible BPA migration into canned foods. This is due largely to the fact that BPA is used as a material for the production of epoxy resins. These resins are used in many professional industries, such as automotive and aviation, but in also the food industry for coating the metal can surfaces which are in contact with food and beverages. Because canned foods are sterilized in the production process, the possibility of BPA migration from the can is high. Indeed, several recent studies that focused on Mexican, Canadian and Belgian markets have shown high amount of BPA leaching from in canned food and coffee products. This study looks at the amount of BPA leaching into canned food products available in the American market. In particular, we examined canned tuna, tomato sauce, and ready‐to‐eat soups and baby formula. The method we use to test these products is based on an indirect enzyme‐linked immounosorbent assay (ELISA), which is highly specific to BPA and allows us to test this chemical directly on the samples without the need of complicated extraction. Preliminary analysis of results and discussion of the proper controls for this study will be presented. Grant Funding Source : Supported by the Rose M. Badgeley Charitable Trust
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".