Multiple gene genealogies reveal important relationships between species of<i>Phaeophleospora</i>infecting<i>Eucalyptus</i>leaves
Bibliographic record
Abstract
The majority of Eucalyptus species are native to Australia, but worldwide there are over 3 million ha of exotic plantations, especially in the tropics and subtropics. Of the numerous known leaf diseases, three species of Phaeophleospora can cause severe defoliation of young Eucalyptus; Phaeophleospora destructans, Phaeophleospora eucalypti and Phaeophleospora epicoccoides. Phaeophleospora destructans has a major impact on seedling survival in Asia and has not, as yet, been found in Australia where it is considered a serious threat to the biosecurity of native eucalypts. It can be difficult to distinguish Phaeophleospora species based on symptoms and micromorphology and an unequivocal diagnostic tool for quarantine purposes would be useful. In this study, a multiple gene genealogy of these Phaeophleospora species and designed specific primers has been constructed to detect their presence from leaf samples. The phylogenetic position of these Phaeophleospora species within Mycosphaerella was established. They are closely related to each other and to other important Eucalyptus pathogens, Mycosphaerella nubilosa, Mycosphaerella cryptica and Colletogloeopsis zuluensis. The specific primers developed can now be used for diagnostic and screening purposes within Australia.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".