Agronomic considerations for reducing deoxynivalenol in wheat grain
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
Abstract Wheat fields under an array of agronomic practices were studied during harvest across southern and eastern Ontario. Mature wheat grain samples were harvested by hand and analyzed for deoxynivalenol (DON). DON levels from wheat grain samples harvested by hand were likely more representative of levels in the field than samples that are typically harvested by machine. The amount of variation in DON levels associated with year and agronomic effects were calculated from simple linear models. As expected, the largest factor associated with variation in DON levels was the year. Year effects accounted for 48% of the variation in DON levels across all fields during 4 years of the survey, followed by cultivar (27%), and the crop 1 year previous to wheat (14–28% depending on the year). No effect on DON could be detected from other agronomic factors including tillage system, crops planted 3 years before wheat, or type of nitrogen fertilizer applied in the spring. Keywords: deoxynivalenolwheattillagecultivarrotationfertilizer
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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) | 0.000 | 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 it