Per- and Polyfluoroalkyl Substances in Canadian Fast Food Packaging
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide A suite of analytical techniques was used to obtain a comprehensive picture of per- and polyfluoroalkyl substances (PFAS) in selected Canadian food packaging used for fast foods ( n = 42). Particle-induced gamma ray emission spectroscopy revealed that 55% of the samples contained <3580, 19% contained 3580–10 800, and 26% > 10 800 μg F/m 2 . The highest total F (1 010 000–1 300 000 μg F/m 2 ) was measured in molded “compostable” bowls. Targeted analysis of 8 samples with high total F revealed 4–15 individual PFAS in each sample, with 6:2 fluorotelomer methacrylate (FTMAc) and 6:2 fluorotelomer alcohol (FTOH) typically dominating. Up to 34% of the total fluorine was released from samples after hydrolysis, indicating the presence of unknown precursors. Nontargeted analysis detected 22 PFAS from 6 different groups, including degradation products of FTOH. Results indicate the use of side-chain fluorinated polymers and suggest that these products can release short-chain compounds that ultimately can be transformed to compounds of toxicological concern. Analysis after 2 years of storage showed overall decreases in PFAS consistent with the loss of volatile compounds such as 6:2 FTMAc and FTOH. The use of PFAS in food packaging such as “compostable” bowls represents a regrettable substitution of single-use plastic food packaging.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".