Diverging fates of cadmium and glyphosate during pasta cooking
Bibliographic record
Abstract
Durum wheat cultivars with varying abilities to accumulate cadmium were grown and treated in the field with a glyphosate-containing herbicide at different stages of maturity to produce grain with higher and lower concentrations of cadmium (0.066-0.214 mg/kg) and glyphosate (0.474-0.874 mg/kg). The grain was milled, and fractions were analysed for cadmium and glyphosate. The highest concentrations for both cadmium and glyphosate were associated with bran and shorts, although the percentage of total cadmium mass in bran (23-25%) was less than glyphosate (38%). The preparation of dried pasta from semolina and flour milling fractions reduced concentrations by a factor of 1.8 for glyphosate and 1.4 for cadmium. Dried pasta was cooked and analysed along with the cooking water for cadmium and glyphosate at seven-time points from 0 to 15 min. Concentrations of glyphosate in cooked pasta decreased significantly with cooking time; no decrease was observed for cadmium concentrations. Analysis of cooking water demonstrated that glyphosate migrated from pasta to the cooking water. After 15 min of cooking, approximately 73% of the total glyphosate mass had transferred from pasta to cooking water. Over the same time period, only 5% of the total cadmium mass had transferred from pasta to cooking water.
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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) | 0.000 | 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 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".