Bibliographic record
Abstract
Although aspen shoot blight (ASB), caused by Pollaccia americana Ondrej, is a common disease of trembling aspen ( Populus tremuloides Michx.), its impact is uncertain. Mechanical wounding, previously shown to be a reliable surrogate for ASB infection, was used to assess ASB impact in two experiments. In the first experiment, the effect of date of wounding on impact was studied by wounding 1-year-old aspen on four dates between 29 June and 10 August 2001. Tree form at the end of the 2001 growing season varied with wounding date, and for each of the wounding dates, tree height was reduced relative to that of unwounded, control trees. After the 2005 growing season, only trees wounded on 17 July were shorter than unwounded trees and the difference in heights was only 62 cm. In the second experiment, trees spaced at 2.0 or 0.67 m were wounded in four successive seasons to determine the effect of multiple years of infection on trees growing at different densities. Simulated ASB reduced tree height by an average of 16 cm, whereas branchiness was not increased by ASB, even at the lower density. Although ASB should not be ignored, these results suggest that it is unlikely to be amongst the most destructive pests of intensively managed aspen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".