Differences in Aceria tosichella population responses to wheat resistance genes and wheat virus transmission
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 Severe winter wheat yield losses due to infestations of wheat curl mite, Aceria tosichella Keifer, and mite-transmitted viruses occur in wheat production areas of the United States and Canada. Mite infestation alone causes stunted, chlorotic plants in susceptible wheat varieties, and mites transmit Wheat Streak Mosaic (WSMV), High Plains Wheat Mosaic (HPWMoV), and Triticum Mosaic Virus (TriMV). Wheat curl mites were collected from 25 sites in Kansas, Missouri, Nebraska, Texas, North Dakota, and South Dakota in 2014 and 2015. At each site, mite virulence was determined to wheat plants harboring the Cmc2 -, Cmc3 -, or Cmc4 mite resistance gene; or Cmc4 plus the Wsm2 WSMV resistance gene. Mites collected from 92%, 36%, and 24% of sites were virulent to susceptible Jagger wheat plants (no Cmc ), Cmc2 , and Cmc3, respectively. The mega-population consisting of all 25 mite sub-populations was avirulent to 80% of plants containing Cmc4 + Wsm2 or Cmc4 . WSMV, HPWMoV, or TriMV was present in mites at 76%, 16%, and 8% of the 25 sites, respectively. Our results will enable breeders to increase the efficiency of wheat production by releasing wheat varieties containing wheat curl mite resistance genes that reduce wheat yield losses.
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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) | 0.001 | 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