The distribution and severity of beech bark disease in the Catskill Mountains, N.Y.
Bibliographic record
Abstract
The distribution and severity of beech bark disease (BBD) in the Catskill Mountains of southeastern New York state, U.S.A., were measured between 1997 and 2000. Forest composition was measured using wedge prism surveys and fixed-area plot counts of canopy species. BBD severity on individual trees was ranked from 1 (no disease) to 5 (dead) based on bark health and canopy loss. These data were analyzed at multiple spatial scales to determine possible controls of disease distribution and severity. BBD was present on almost all Fagus grandifolia Ehrh. (American beech) individuals encountered >10 cm diameter at breast height, but was most severe in larger diameter classes. Mortality due to BBD also increased with diameter class. A strong positive relationship was found between BBD severity and relative beech basal area at the tract (hundreds of hectares) and 100-m elevation band spatial scales, but not found at smaller scales. Successful long-range dispersal of the disease may therefore be dependent upon host density, while local conditions may control BBD severity within individual stands. The current status of BBD in the Catskills suggests these forests are entering the aftermath phase of the disease's progression and that BBD has become an endemic component of these forests.
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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 | 0.001 |
| 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".