Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. The Avalanche Terrain Exposure Scale (ATES) is a classification system that communicates avalanche terrain severity to different target audiences. ATES is a static terrain rating method that is independent of avalanche hazard, so the ratings do not change with the weather and snow conditions. The system was originally introduced in Canada in 2004 as a risk management tool for public avalanche safety programs and uses two synonymous methods: one for terrain assessment and another for public communication. The ATES method applies technical specifications for assessing avalanche terrain to determine ratings, and it is paired with communication models to convey those terrain ratings to different user groups. ATES ratings are found in guidebooks and route descriptions or are displayed spatially as zones on a map, and they have been widely applied to public safety programs and workplace avalanche safety plans. This paper introduces ATES v.2, a revised and updated system that merges the two previous ATES models into a single method that (1) expands the original version from three levels to five by including Class 0 (Non-avalanche terrain) and Class 4 (Extreme terrain), (2) removes glaciation as an input parameter, and (3) introduces a communication model for waterfall ice climbing. The ATES technical specifications are reviewed in detail, along with guidance on their application by field-based practitioners and desktop-based Geographic Information System (GIS) users. The use of both manual and automated ATES assessment methods is discussed, along with methods for presenting ATES ratings to the target audience. This paper addresses a gap in the literature with respect to avalanche terrain classification for backcountry travel. After 20 years of use in different jurisdictions and countries, the ATES method has not yet been published in a peer-reviewed journal. This publication seeks to correct that and establish a baseline reference for ATES upon which future terrain-based products and research can build.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 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 it