Physiologic specialization of wheat leaf rust (<i>Puccinia triticina</i>) in Canada in 2002
Bibliographic record
Abstract
Forty virulence phenotypes of Puccinia triticina were identified from 295 isolates collected across Canada in 2002 on 16 Triticum aestivum ‘Thatcher’ near-isogenic lines. The most frequent virulence phenotypes across Canada were MBDS (30.2%), TGBJ (22.0%), TBBJ (9.5%), and TBDS (7.8%). There were 10 virulence phenotypes identified among 24 isolates from Quebec; MBRK (29.2%), TBRJ (16.7%), MBRJ (12.5%), and TLGJ (12.5%) were the most frequent. Ten virulence phenotypes were identified among 22 isolates from Ontario, with PCLR and PCMR (both 22.7%) being the most frequent. There were 25 virulence phenotypes identified from 234 isolates collected in Manitoba and southeastern Saskatchewan; MBDS (32.9%), TGBJ (27.4%), and TBBJ (11.5%) were the most frequent. The frequency of virulence to Lr16 declined in Manitoba and Saskatchewan from 74.1% in 2001 to 33.3% in 2002 while the frequency of virulence to Lr17 increased from 23.8% in 2001 to 53.4% in 2002. Five virulence phenotypes were identified from 15 isolates collected in Alberta. These were MBDS (11 isolates), TBBJ, TBDS, TCRK, and TGBJ (all one isolate each). A subsample representative of the field isolates collected in 2002 was tested for virulence on adult plants. All 71 isolates tested were avirulent to adult-plant resistance genes Lr22a, Lr34, and Lr3, and to seedling genes Lr21 and Lr32 which are best expressed in adult plants. The isolates varied for virulence to adult-plant resistance genes Lr12 and Lr37, and only one isolate was avirulent to Lr13.
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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".