Physiologic specialization of<i>Puccinia triticina</i>in Canada in 2005<sub>1</sub>
Bibliographic record
Abstract
Collections of Puccinia triticina, the causal agent of wheat (Triticum aestivum) leaf rust, were sampled across Canada in 2005 to determine the virulence spectrum of this pathogen and detect changes in virulence to important resistance genes. Forty virulence phenotypes were identified from 420 P. triticina isolates. Four virulence phenotypes, MBBJ, NBBR, TDBG, and TLGJ, were identified from five isolates collected in Quebec and six virulence phenotypes, MBJD, MCDS, MCPS, MFDS, MFPS, and TCTF, from six isolates from Ontario. Thirty-five virulence phenotypes were identified from the 396 isolates collected in the eastern prairie region (Manitoba and eastern Saskatchewan) of Canada, with TDBG (46.7%), TBBG (10.9%), and TDBJ (9.1%) being the most common phenotypes. Virulence phenotypes TDBG and TBBG and other similar phenotypes found in high frequency in 2005 had some unusual virulence characteristics, including avirulence to LrCen, Lr14a, and Lr20, which had previously been rare in Canada. Four virulence phenotypes, MBBJ, MBDS, MBGJ, and MBPS, were identified among 13 isolates from Alberta or British Columbia. Of 81 representative isolates, 74, 77, 4, and 67 isolates were virulent to wheat lines with the adult plant resistance genes Lr12, Lr13, Lr35, and Lr37, respectively. None of these were virulent to Lr22a. When tested on an extended set of wheat leaf rust differentials, 46, 43, 74, 60, 51, and 39 of the 81 isolates were virulent to the seedling resistance genes Lr3bg, Lr14b, Lr15, Lr20, Lr23, and Lr28, respectively, yet no virulence was detected to Lr19, Lr21, Lr25, Lr29, or Lr32
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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) | 0.001 | 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 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".