Bibliographic record
Abstract
Abstract. The Avalanche Terrain Exposure Scale (ATES) is an avalanche terrain classification system used to assess and communicate the exposure of backcountry terrain to the threat from avalanches, independent of daily hazard conditions. Commonly known as terrain ratings, these classifications are determined by an analysis of individual terrain parameters, which are then systematically combined to produce a single rating. The ATES model includes technical specifications for assessing terrain as well as corresponding communication scales for effectively sharing ratings with different kinds of backcountry users. ATES ratings are found in guidebooks and route descriptions or displayed spatially on maps. The system was originally introduced in Canada in 2004 as a risk management tool in conventional avalanche safety practices for public recreation and workplace avalanche safety. This paper introduces ATES v.2, an update to the system that expands the original scale from three levels to five by including Class 0 – Non-Avalanche Terrain, and Class 4 – Extreme Terrain. The original ATES v.1/04 and the ATES Zoning Model are merged into a single, five-level, updated version of ATES. ATES ratings can be applied as Areas, Zones, Corridors, or Routes and then communicated using models for backcountry travel and waterfall ice climbing.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".