Dry snow slab quasi‐brittle fracture initiation and verification from field tests
Bibliographic record
Abstract
Dry snow slab avalanches initiate from shear fracture in a thin weak layer underneath a planar slab of cohesive snow. In this paper, field data from more than 400 snow shear fracture tests are analysed and applied to the problem of snow slab release and snow pack instability evaluation. The paper contains a new, but simple, analytical model to estimate the critical length for fracture. The model contains the assumption of a finite fracture process zone which may be a significant fraction of the slab depth D or the critical length L for weak layer shear fracture. The results suggest that the ratio L/D is of order 1 for both the data and the model as previously predicted for the snow slab. Using a combination of experimental results from laboratory tests, two sets of field data and the new model, suggests that previous theoretical arguments about snow slab release over almost 30 years are congruent with the field data. Simple extension to explain viscoelastic temperature effects and slope normal weak layer deformation on snow slab instability evaluation is included in the analysis. Since the experimental field data contain viscoelastic effects and slope normal effects, it is imperative to account for these in the model and for snow slab instability evaluation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".