Bibliographic record
Abstract
Avalanches which occur during periods of cooling are important because they can surprise people, even very experienced practitioners. However, the influence of cooling on avalanche activity has not been well studied and is poorly understood. A survey of 40 avalanche professionals indicates that avalanches sometimes occur when the snow surface is cooling from above-freezing to below-freezing, often leading to unexpected and very large slab failures. Around 360 avalanches were reported from New Zealand, North America, Europe, Asia and Antarctica when snow surface temperatures dropped from 0° C to below 0° C. An avalanche of this type is termed a ‘Cool-Down Avalanche’ (CDA). This dataset, which spans the years 1960-2010, has been analysed to illustrate common snowpack and meteorological characteristics during CDA activity. The survey revealed that avalanches also occur during times of rapid cooling within an overall colder temperature regime, without a clear melt-freeze process at the snow surface. Case studies from western Canada during the 2010-2011 winter give examples of avalanches which occurred under such a regime. Challenges for forecasting cooling-related avalanches are discussed.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".