Determination of Deoxynivalenol in Soft Wheat by Immunoaffinity Column Cleanup and LC-UV Detection: Interlaboratory Study
Bibliographic record
Abstract
An interlaboratory study was conducted to assess the applicability of a previously validated method for the analysis of deoxynivalenol (DON) in cereal and cereal products to soft wheat in the range of >0.1-3.0 microg/g. The study evaluated a generic method to determine DON at levels that bracket the existing Canadian guidelines for DON in soft wheat destined for use in baby foods and nonstaple foods. Collaborators selected one of 2 approved brands of DON immunoaffinity column for cleanup and their choice of qualified C18 liquid chromatographic (LC) column. Separation was by LC with UV detection. Blind duplicates from 5 levels of naturally contaminated wheat and a pair of spiked wheat samples were successfully analyzed by 12 laboratories in 8 countries. For samples naturally contaminated with DON from <0.1-2.2 microg/g, the relative standard deviation of repeatability (RSDr) ranged from 3.1 to 14.8%. For reproducibility, the RSDR ranged from 21.0 to 32.9% and the HorRat range was 1.0 to 1.9. Recoveries of 0.5 microg/g DON spiked into wheat ranged from 66 to 98%, with an average of 84%. The RSDr was 5.4%, the RSDR was 12.6%, and the HorRat value was 0.7.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".