Trends in acrylamide content in selected potato/sweet potato products on the Canadian market
Bibliographic record
Abstract
Processed plant-based foods, particularly high carbohydrate-containing foods, are among the greatest contributors to dietary acrylamide, a probable human carcinogen, uptake. Between 2009 and 2020, five surveys were conducted to determine acrylamide in high carbohydrate-containing foods in Canada. These surveys included sampling of potato and sweet potato chips, French fries, and frozen potato/sweet potato products, as a follow-up to our earlier surveys from 2002 - 2008. Samples were analyzed using isotope dilution (13C3-acrylamide) with LC-MS/MS. The highest mean acrylamide levels were found in sweet potato chips. Among potato chips (57 to 4660 ng g−1), one brand consistently showed the highest concentrations with wide variability. Acrylamide concentrations decreased over time in ready-to-eat French fries (from 480 to 358 ng g−1), and one brand showed a clear reduction temporally. Wide variations were observed among brands, among lots/outlets of same brands, and among different food chains. Acrylamide levels in potato chips decreased between 2009 and 2016 (504.3 ng g−1) relative to the period 2002 - 2008 (1096.9 ng g−1). The acrylamide trends observed in the products measured in the latest study indicate that food producers may have adopted mitigation strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".