An Avalanche Terrain Assessment of Proposed Manitoba Mountain and Whistle Stop Hut-to-Hut Systems Using a Geographical Information System
Bibliographic record
Abstract
Alaska Mountain and Wilderness Hut Association has proposed a hut-to-hut system on the Kenai Peninsula of Southcentral Alaska. A terrain assessment is first of several steps necessary before construction of huts begins. Locating huts in this remote area may increase the use of the area, with potential for an increase in less skilled users. It is important to provide all recreational users with safe routes and safes resting locations. A model was created to determine the amount of terrain in potential release areas. An equation was applied to the ridgelines above proposed hut sites to estimate potential run-out distances of slides. Results were compared to actual historical run-out in the area observed by the Alaska Railroad. All of this was calculated and displayed using both a GIS and knowledge of avalanche terrain. Raster data available for this area, and most of Alaska, has a fairly large cell size so many micro-terrain features are missed in the assessment. As a result of the cell size limitations there is a need for further study of these areas including field observations. Outlined in the following article is a preliminary assessment of the avalanche terrain along the proposed hut-to-hut systems at Manitoba Mountain and along the Whistle Stop route.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".