Snow avalanche penetration into mature forest from timber-harvested terrain
Bibliographic record
Abstract
Clear-cut logging in British Columbia, Canada, is creating new avalanche start zones from which snow avalanches sufficient in size to penetrate and destroy mature forest cover can initiate. In addition to creating new start zones, the presence of these logging cut blocks can augment the destructive potential of previously existing avalanche paths. Forest-penetrating avalanches can pose a significant risk to down-slope structures and resources. This study is the first to develop and utilize a database containing information on penetration distances and lateral spread from avalanches that have penetrated forest cover. The study area for this research spans the Southern Coast and Columbia Mountains of British Columbia, Canada. Analysis focuses on terrain characteristics related to forest penetration and the resultant destruction of mature standing forest. Physical terrain and vegetation characteristics in the avalanche starting zone, track, and runout zone of 45 forest-penetrating avalanches are described, measured, and parameterized. The results provide tools to assess and evaluate potential forest-penetrating avalanche terrain, and runout models for avalanches in forested terrain.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".