A Solar Warming Model (Swarm) to Estimate Diurnal Changes in Near-Surface Snowpack Temperatures for Back-Country Avalanche Forecasting
Bibliographic record
Abstract
ABSTRACT: Diurnal temperature fluctuations occur in near-surface snowpack layers as a result of the energy balance at the snow surface. While there is some understanding of these temperature fluctuations and their effects on snowpack stability, quantified estimates of their magnitude are not readily available to avalanche forecasters in western Canada. During the winters of 2005 and 2006, near-surface temperatures were measured on a knoll located in the Columbia Mountains of British Columbia. The field dataset was used to develop a near-surface warming model, based on linear regression analysis of predictor variables derived from surface energy flux terms. To facilitate use in large forecast areas where representative meteorological data are typically scarce, consideration was given to the availability of input data. Based on slope, aspect, expected cloud cover and number of days since snowfall, the model predicts the magnitude of near-surface daytime warming with an estimated root mean square error of 1.6 ºC.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".