Evaluation of the Fate of Ice Storm-Damaged Urban Maple (Acer) Trees
Bibliographic record
Abstract
Annually, ice storms cause millions of dollars of damage to urban trees and infrastructure in the United States and Canada. However, there is limited information to guide judgments on whether to remove ice-damaged trees. This study followed the response of three maple species that were damaged in the 1998 ice storm in northern New York State. Norway (Acer platanoides), silver (A. saccharinum), and sugar maples (A. saccharum) were placed in one of three diameter classes and canopy loss categories and were reevaluated 6 years after the initial damage. Over the 5-year study period, 26.8% of trees were removed, and there was no statistical difference among species, crown loss, or diameter class for these removals. Analysis of a variety of tree health and crown parameters showed that tree species was the most important factor in response, whereas diameter class and crown loss were less important. These results suggest that urban tree managers should consider tree species as an important factor in making removal decisions after an ice storm.
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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) | 0.000 | 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".