Hurricane Igor Impacts at Northern Latitudes: Factors Influencing Tree Fall in an Urban Setting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hurricane Igor was a Category 1 hurricane when it passed the island of Newfoundland, Canada, causing extensive damage. Hurricanes are uncommon at northern latitudes, and boreal species are not adapted to hurricane-force winds. Moreover, much of the storm damage was in the urban area of the City of St. John’s, where there are also numerous non-native trees. This research tested whether there were attributes of trees (e.g., height, diameter at breast height, slenderness, species, age, or distance to nearest tree) that may have influenced whether a tree fell or was left standing. The study authors sampled 70 trees and found that DBH was a significant predictor of tree fall (snapping or uprooting). Conifers were no more or less likely to fall in the storm than deciduous trees, nor were native trees more or less susceptible to wind damage than non-natives. These results suggest that for a boreal, urban ecosystem, there are no target species available that could be planted strategically to minimize risk of tree fall in a major wind event. Thus, to minimize storm damage to human-built infrastructure in regions where hurricanes are rare, the best strategy would be to avoid having large trees located in close proximity to infrastructure.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it