Observation and modeling of a buried melt-freeze crust
Bibliographic record
Abstract
ABSTRACT: Melt-freeze crusts often occur as a result of wet snow, rain or strong insolation. Past observations have revealed the formation of weak layers at their boundaries, even when the depth-averaged temperature gradient favours rounding. Research has, however, predominantly targeted temperature regimes dominated by kinetic growth. During the winter of 2007-2008 University of Calgary researchers undertook systematic observations of the early December melt-freeze crust that was present throughout much of Western Canada. The data gathered included ongoing measurement of the temperature gradient across the crust, snow load and shear strength. These observations were used along with meteorological measurements to drive the Swiss SNOWPACK model, a physically based single column model which sim-ulates the evolution over time of a number of microstructural and mechanical properties of the snowpack. We present here the observations from the first year, initial efforts to identify parameters with the greatest influence on mechanical properties and results from model simulations.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".