Bisphenol A in Baby Food Products in Glass Jars with Metal Lids from Canadian Markets
Bibliographic record
Abstract
A method based on solid phase extraction and derivatization with acetic anhydride followed by gas chromatography-mass spectrometry was validated for the determination of bisphenol A (BPA) in baby foods. The average method detection limit (MDL) was 0.18 ng/g for a 5 g sample. Method repeatability was demonstrated with the replicate analyses of various different types of baby foods; relative standard deviations (RSD) ranged from 1.2 to 16.1% with an average of 8.7%. Extraction recoveries ranged from 93.5 to 102.5% for different types of baby foods spiked at levels of 1-8 ng/g. This method was used to analyze 122 baby food products of 7 brands in glass jars with metal lids for BPA. The presence of BPA could not be confirmed and quantified for 23 of the 122 products due to interference from sample matrices. For the other 99 products, 15% had BPA levels of less than the average MDL, about 70% had BPA levels of less than 1 ng/g, and the average BPA levels in all 99 products was 1.1 ng/g. The average BPA level in the baby food products from brand E (3.9 ng/g) is higher than the average BPA levels in the products from the other brands (0.54-1.1 ng/g). The highest level of BPA, 7.2 ng/g, was found in two products from brand E as well. The average BPA level in the fruit products from all brands (0.60 ng/g) is lower than those in the mixed-dish products (1.1 ng/g) and the vegetable products (1.2 ng/g).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".