Acrylamide in Foods: Occurrence, Sources, and Modeling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it