LC-MS/MS analysis of bisphenol S and five other bisphenols in total diet food samples
Bibliographic record
Abstract
It is already known that bisphenol S (BPS) has been used as a substitute for BPA in thermal papers in recent years. It is not clear, however, if BPS has also been used to replace BPA in can coatings as currently being speculated due to a lack of credible studies on migration of BPS from can coatings and occurrence data of BPS in foods. In this study, an LC-MS/MS method was developed for the analysis of BPS, along with several other bisphenols, and method detection limits for BPS varied from 0.0017 to 3.1 ng/g depending on the type of sample matrix and the amount of sample analysed. This method was used to analyse 159 different food composite samples from a recent Canadian total diet study. Bisphenol E (BPE), bisphenol B (BPB), and bisphenol AF (BPAF) were not detected in any of the 159 food composite samples, bisphenol F (BPF) was detected in only three samples (25-2360 ng/g), and bisphenol A (BPA) was detected in 10 samples (5.3-41 ng/g) which were all prepared from canned foods. BPS was not detected in any of the canned food composite samples but was detected in nine food composite samples prepared from meat and meat products (1.2-35 ng/g), indicating sources for BPS other than can coatings may be possible, which will be investigated in future studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 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) | 0.003 | 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".