Bibliographic record
Abstract
The distribution of avalanche runout varies in space and time for individual avalanche paths and from mountain range to mountain range. In this paper, such variations are considered based on the assumption (supported by data worldwide) that the spatial distribution of extreme avalanche runout follows a Gumbel distribution and that the arrival rate of avalanches can be modelled as a Poisson process. The input required is a set of extreme avalanche runout distances for the mountain range and a knowledge of avalanche frequency at the beginning of the runout zone for the path in question. Such information allows theoretical estimation of the effective return period as a function of position, which is very important in zoning applications. In addition, general expressions are derived to relate Gumbel parameters for different mountain ranges to a frequency index to explore general frequency implications from one mountain range to another. The estimated Gumbel parameters imply consistent relationships for expected avalanche frequency and terrain from one mountain range to another.Key words: snow avalanches, runout distances, return period, frequency, 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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".