Statistical avalanche-runout estimation for short slopes in Canada
Bibliographic record
Abstract
Abstract To develop avalanche runout models for short slopes, field measurements were made at 48 short-slope avalanche paths located in the Coast, Columbia and Rocky Mountains of western Canada, and at several paths in eastern Canada. Field studies included detailed topographic surveys and estimation of the extreme runout position in each path. A statistical runout model was developed using the runout ratio method, for which runout ratios from the four mountain ranges are well fit by an extreme-value type I (Gumbel) distribution when the β point is defined at the uppermost point where the slope is 24°. A second model was developed by regressing the α angle for the extreme runout position on numerous terrain variables. This regression model uses three predictor variables that can be easily measured in the field or on topographic maps. Length-scale effects were noted in both models, but are more pronounced in the runout ratio model. A comparison of models developed using the two methods shows that the runout ratio model estimates more conservative (longer) runout distances than the regression model for most threshold probabilities. Data from 13 additional paths from Switzerland and Québec, Canada, are used to test the models.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".