Physiologic specialization of<i>Puccinia triticina</i>, the causal agent of wheat leaf rust, in Canada in 2003
Bibliographic record
Abstract
Twenty-three virulence phenotypes, based on the infection types produced on 16 wheat differential lines, were identified from 97 isolates of Puccinia triticina, the causal agent of leaf rust on wheat, collected across Canada in 2003. Virulence phenotypes MCJJ, SBDJ, and TJBJ from Quebec were identified. Seven virulence phenotypes (MBDS, MBJS, TLGJ, MBPS, MBRJ, TBBJ, and TBRK) were detected among 13 isolates from Ontario. Twelve virulence phenotypes were detected among 73 isolates from Manitoba and Saskatchewan; the most prevalent were TBBJ, MBDS, and KBBJ. There was a decline in the frequency of virulence to Lr16 in Manitoba and Saskatchewan from 33.3% in 2002 to 4.1% in 2003. Six virulence phenotypes (BBBN, LBDS, MBBJ, MBDS, TBDJ, and TJBJ) were identified among seven isolates from Alberta. Among 29 isolates, representative of most virulence phenotypes tested on additional differentials, 13, 25, 27, 27, 17, and 14 isolates were virulent to seedling plants with Lr2b, Lr3bg, Lr14b, Lr20, Lr23, and Lr28, respectively. No isolates were virulent to Lr19, Lr21, Lr25, Lr29, or Lr32, while all isolates were virulent to Lr15. There were 24, 24, 1, 22, and 28 isolates virulent to adult plants with Lr12, Lr13, Lr35, Lr37, and to 'Thatcher', respectively, but none were virulent to Lr22a or Lr34.
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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 | 0.001 |
| 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".