Applying the avalanche terrain exposure scale in the Swiss Jura mountains
Bibliographic record
Abstract
The avalanche terrain exposure scale (ATES) was developed by Parks Canada in 2004 as a\ncomplementary tool to increase awareness and to communicate the risks encountered when travelling in\navalanche terrain. In the meantime, many popular backcountry tours in Canada were rated. More recently,\nATES has also been applied in some European countries. We review existing ATES applications\nas well as other alpine tour rating systems. An adaptation of ATES for a new application in the Swiss\nJura, a popular area for snow shoeing and ski touring, is presented. The Jura hills are a low mountain\nrange along the north-western border of Switzerland. There are about 60 popular tours in mostly gentle\nterrain, yet exposure to avalanche terrain also exists in some locations. We elaborate the requirements of\na terrain classification in our particular low mountain range environment. As a result, the adapted technical\nmodel and public communication model as well as tour examples from the Swiss Jura are shown. A\ncommunication strategy is developed to increase the applicability and acceptance of the classification in\nSwitzerland. A potential expansion to the Swiss Alps is discussed.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".