Bibliographic record
Abstract
Melt-freeze crusts are one of the most critical layers for slab avalanche formation. These layers usually undergo complex metamorphism and associated snow cover stability may increase or decrease over time. Typical field observations are of a subjective nature and hence tracking changes to these layers can be inconsistent amongst multiple observers. In order to improve the way melt-freeze crusts are observed we present three tracking systems used over the 2011-12 winter season: a set of quantitative measurements, a simple new crust index (CI), and the use of a thermal imager. During the winter season 2011-12, six melt-freeze crusts were tracked over time with these methods in the Columbia Mountains, British Columbia, Canada. The physical properties of a melt-freeze crust can be best described using a set of quantitative measurements shear frame, push gauge and density – but these may be operationally impractical. The crust index consists of two parts: the first part describes the bonding at the upper and lower interface of a melt-freeze crust; the second part describes the internal lamination or bonding within the crust. In addition, a thermal camera was used to measure small scale temperature gradients. This allowed us to monitor changes in the temperature gradient over time above and below melt-freeze crusts.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".