CROP: Wheat LOCATION: Ontario NAME AND AGENCY
Bibliographic record
Abstract
METHODS: Winter wheat fields were randomly selected at harvest on farms across Ontario. Mature wheat spikes were harvested using hand shears from 10 areas of approximately 2m2 close to the center of each field. The spikes were threshed with an Almaco stationary plot thresher (model VPT-OSC). Deoxynivalenol (DON) content was estimated using a quantitative fluorometric test-FluoroQuan (Romer ® Labs, Inc, Union MO). Sixty kernels per field were surface-sterilized in 0.16 % NaOCl (diluted commercial bleach) for three minutes, air dried and placed on acidifed potato dextrose agar. The agar plates were incubated for seven days under a 12:12 hr light/dark cycle, at room temperature and Fusarium spp. were counted. F. graminearum colonies were transferred to carnation-leaf agar, incubated as above and identified based on Nelson et al. (1983). RESULTS AND COMMENTS: The highest DON content (ppm) were observed in Essex county (averaging 4.9 ppm), followed by Kent, Elgin and Middlesex counties with DON values, 2.4, 2.0 and 1.7 ppm respectively (Table 1). Level of Fusarium damage kernels (FDK) ranged from 0.7 % in Bruce county to 3.0 % in Kent and Middlesex counties. Highest % of F. graminearum colonies (20.7%) was isolated from Elgin
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.054 | 0.013 |
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".