<i>Leptosphaerulina australis</i>associated with intensively managed stands of<i>Poa annua</i>and<i>Agrostis palustris</i>
Bibliographic record
Abstract
Leptosphaerulina leaf blight has been sporadically documented affecting turfgrasses. Recently, a Leptosphaerulina species has been seen on diseased turfgrass samples from New England and New York State. In all cases where Leptosphaerulina has been observed in New England, it has been accompanied by a number of other turf pathogens on highly stressed hosts, so its pathogenic potential has been unclear. The purpose of this study was to identify isolates to species, determine their pathogenicity in the greenhouse, and characterize their fungicide sensitivity in vitro in the event that significant pathogenicity was demonstrated. Microscopic observation of spores and culture characteristics indicated that all examined isolates were Leptosphaerulina australis. The optimum temperature for growth was assessed and the relationship between temperature and sporulation was examined. After repeated experiments utilizing several grass species under a variety of environmental conditions, all four isolates examined were determined to be nonpathogenic. Isolates produced pseudothecia on senescent tissue but infection of live tissue was never observed. The fungicide sensitivity assay demonstrated significant variation among isolates. Based on the results of this study and other observational evidence, it is likely that this species is saprobic on senescent turfgrass leaves but not pathogenic.
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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 | 0.001 | 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".