Physiologic specialization of<i>Puccinia triticina</i>, the causal agent of wheat leaf rust, in Canada in 2004
Bibliographic record
Abstract
Virulence surveys are conducted annually in Canada on the pathogen causing leaf rust in wheat, Puccinia triticina, to monitor changes in the population and to quickly detect the development of virulence to important resistance genes in wheat. Forty-six virulence phenotypes were identified in 2004 from 330 P. triticina isolates, on the basis of their reactions to 16 wheat differential lines. There were 9 virulence phenotypes among 15 isolates from Quebec and 12 virulence phenotypes among 16 isolates from Ontario. There were 24 virulence phenotypes among 281 isolates from Manitoba and Saskatchewan, where the most frequently isolated were TBBJ (48.0%), TBBG (17.4%), and MBDS (10.0%). Each of the 3 isolates from Alberta possessed a unique virulence phenotype and there were five virulence phenotypes among 15 isolates from British Columbia. Only 3.9% of the isolates collected in 2004 were virulent to Lr16, which constituted a much lower percentage than in previous years. When a subset of 58 representative isolates was tested on adult plants, there were 47, 55, 0, 2, and 46 isolates virulent to the adult-plant resistance genes Lr12, Lr13, Lr34, Lr35, and Lr37, respectively. This subset of isolates varied for virulence on additional differentials tested at the seedling stage, with 30, 41, 18, 39, 26, 1, and 35 isolates virulent to Lr3bg, Lr14b, Lr15, Lr20, Lr23, Lr25, and Lr28, respectively.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".