A potential microbial control for fireweed (Epilobium angustifolium)
Bibliographic record
Abstract
Diseased fireweed (Epilobium angustifolium) plants were collected in Quebec and organisms isolated from these plants were evaluated as potential biocontrol agents. Thirteen pathogenic fungi were isolated and three of these (Colletotrichum dematium, Seimatosporium kriegerianum, and Alternaria alternata) were virulent in initial screening assays. C. dematium was selected for further study because it was the most virulent pathogen, causing large necrotic lesions on leaves and stems of infected plants. Inoculum production was optimized on modified malt extract agar and the virulence enhanced by suppression of the conidial matrix with tannic acid and the addition of extracts of Aloe saponaria. The fungus was pathogenic to fireweed and E. lanceolatum, while other test species were very resistant or immune. Measurements of conidial and appressorial dimensions and its restricted host range support the hypothesis that the isolate may be an unreported form-species. Application of formulated conidia consistently provided 100% mortality of 7-wk-old inoculated fireweed rosettes within 48 h using 109 conidia m-2, from 10- to 15-d-old inoculum, and a 18- to 24-h dew period. Virulence was diminished in older plants. In field trials, growth of inoculated rosettes was reduced by 33%. These results suggest that C. dematium is a promising candidate for further development as a control agent for seedling fireweed in silviculture.
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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 | 0.000 | 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".