Induced glide-snow avalanches with low friction geotextiles
Bibliographic record
Abstract
Gliding snow avalanches are of growing concern for the management of ski areas, transport corridors and spatial planning. With a warming climate there appear to be increasing reports of gliding snow hazards in alpine regions. The management of gliding snow avalanches can be achieved through either stabilization or artificially triggering a slide. Triggering sliding is attractive because it has the potential to remove the hazard entirely. In this research, we investigate the potential of managing gliding snow avalanches through the early release of snow accumulations using low friction geotextiles. A series of geotextiles have been installed on slopes between 25 and 35° during the autumn months and the behavior of snow accumulations observed during the winter. Initial findings indicate that reducing the basal friction can be effective in inducing early release of gliding snow avalanches. However, the interaction of the flanking snow pack and stauchwall appear dominant in the behavior of the system. This contribution reports on the initial findings of these experiments and discusses the potential applications to managing gliding snow avalanches.
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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 | 0.001 |
| 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".