Current sampling plans can introduce high variance in mycotoxin testing results as demonstrated by the online FAO Mycotoxin Sampling Tool
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
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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