Stem Rust Resistance: Two Approaches
Bibliographic record
Abstract
Stem rust, caused by Puccinia graminis f.sp. tritici ( Pgt ), is a destructive disease of wheat that has historically caused significant yield losses in much of the global wheat production area. Over the past 50 years, stem rust has been effectively controlled by deploying cultivars carrying stem rust resistance ( Sr ) genes. With the emergence of new Pgt races, namely Ug99 and its variants, there has been a reinvestment in stem rust research. This includes discovery, characterization, genetic mapping, and cloning of Sr genes. Here we investigated two such examples of genetic characterization and mapping of stem rust resistance. In the first example, a region on chromosome 6DS harbouring resistance to Ug99 was examined in several populations and from several sources. In the second example, a less typical genetic model of resistance was studied in which seedling resistance was activated by an independent locus exhibiting an apparent “nonsuppressing” effect. The knowledge gained by these and other lines of research will contribute to the goal of durable resistance to stem rust. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".