Acrylamide in Foods: Occurrence, Sources, and Modeling
Bibliographic record
Abstract
Acrylamide in food products-chiefly in commercially available potato chips, potato fries, cereals, and bread-was determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Samples were homogenized with water/dichloromethane, centrifuged, and filtered through a 5 kDa filter. The filtrate was cleaned up on mixed mode, anion and cation exchange (Oasis MAX and MCX) and carbon (Envirocarb) cartridges. Analysis was done by isotope dilution ([D(3)]- or [(13)C(3)]acrylamide) electrospray LC-MS/MS using a 2 x 150 mm (or 2 x 100 mm) Thermo HyperCarb column eluted with 1 mM ammonium formate in 15% (or 10% for the 2 x 100 mm column) methanol. Thirty samples of foods were analyzed. Concentrations of acrylamide varied from 14 ng/g (bread) to 3700 ng/g (potato chips). Acrylamide was formed during model reactions involving heating of mixtures of amino acids and glucose in ratios similar to those found in potatoes. In model reactions between amino acids and glucose, asparagine was found to be the main precursor of acrylamide. Thus, in the reaction between nitrogen-15 (amido)-labeled asparagine and glucose, corresponding (15)N-labeled acrylamide was formed. The yield of the model reaction is approximately 0.1%.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".