A new set of international <i>Leptosphaeria maculans</i> isolates as a resource for elucidation of the basis and evolution of blackleg disease on <i>Brassica napus</i>
Bibliographic record
Abstract
Abstract A collection of isolates of the fungi Leptosphaeria maculans and L . biglobosa , which cause blackleg disease on Brassica napus (canola/oilseed rape) and other Brassicaceae species, was assembled to represent the global diversity of these pathogens and a resource for international research. The collection consists of 226 isolates (205 L . maculans and 21 L . biglobosa ) from 11 countries. The genomes of all 205 L . maculans isolates were sequenced, and the distribution and identity of avirulence gene alleles were determined based on genotypic information and phenotypic reactions on B . napus lines that hosted specific resistance genes. Whilst the frequencies of some avirulence alleles were consistent across each of the regions, others differed dramatically, potentially reflecting the canola/oilseed rape cultivars grown in those countries. Analyses of the single‐nucleotide polymorphism (SNP) diversity within these L . maculans isolates revealed geographical separation of the populations. This "open access" resource provides a standardized set of isolates that can be used to define the basis for how these fungal pathogens cause disease, and as a tool for discovery of new resistance traits in Brassica species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".