Current sampling plans can introduce high variance in mycotoxin testing results as demonstrated by the online FAO Mycotoxin Sampling Tool
Bibliographic record
Abstract
The free-to-use online FAO Mycotoxin Sampling Tool ( http://tools.fstools.org/mycotoxins/ ) provides users an opportunity to easily estimate impacts of adjusting sampling plan parameters on the risk of misclassifying consignments relative to a defined maximum level, as well as the contributions from sampling, sample preparation, and analytical test stages to the total variance of mycotoxin sampling plan designs, without performing resource-intensive sampling and laboratory analyses. The Tool was used to assess variance in the analysis of aflatoxins, deoxynivalenol, fumonisins, and ochratoxin A in maize, wheat, and powdered ginger for various sampling plans, including those specified in the Codex Alimentarius Commission General Standard on Contaminants and Toxins in Food and Feed. Results indicated that the current Codex sampling plans for maize and wheat could result in total measurement error equivalent or greater than 90% of the current and proposed maximum levels for ochratoxin A in wheat and aflatoxins in maize, respectively.
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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 | 0.031 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".