Mycotoxins in small grains and maize: Old problems, new challenges
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
This paper reviews the challenges relating to chronic contamination of small grains and maize with deoxynivalenol and related compounds, fumonisin and the use of ensiled cereals in cool dairy areas. Uncertainties in the tolerable daily intakes for deoxynivalenol and fumonisin are discussed as they have the potential to affect current regulatory limits. In addition, climate change is resulting in more extreme rainfall and drought events which favour formation of deoxynivalenol and fumonisin, respectively. The development and refinement of models for predicting mycotoxin accumulation from weather data will become an essential tool for managing these events. Such models are also important for providing timely food aid to developing countries, which experience increased occurrence of acute toxicities, especially in children. Chronic contamination of silage in some areas with some Penicillium toxins deserves more attention in terms of their economic effects and possible implications for the purity of milk.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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