Ice damage impacts on the health of the northern New York State forest
Bibliographic record
Abstract
Detailed crown condition information, including numbers of broken branches ≥ 5 cm diameter, broken tops, and healthy branches, were recorded for 5434 living trees > 9 cm dbh from 603 ten-basal-area-factor prism plots (three per forest stand) at 201 random points (stands) throughout the ice damage region of northern New York State. Twenty five percent of the sample stands had ≥ 20% branch breakage. Bigtooth aspen, red oak, red maple, and white pine had the most breakage. Comparison of potential mortality of trees associated with ≥ 75% ice damage (severe damage) to baseline (predicted) mortality to maintain the existing forest structure suggests that ice damage may alter the health of 18% of the forest stands but this is not sufficient to alter the health (sustainability) of the larger forest system. Key words: ice storm, forest health, sustainability, growth, mortality, dbh classes
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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) | 0.002 | 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".