A higher‐order method for determining quasi‐brittle tensile fracture parameters governing the release of slab avalanches and a new tool for in situ indexing
Bibliographic record
Abstract
The tensile fracture of heterogeneous earth materials such as snow, ice, and rocks can be characterized by two fracture parameters—the fracture toughness and the fracture process zone length. The latter length scale characterizes the zone of microcracking surrounding a crack tip in a heterogeneous material. For alpine snow, these two fracture parameters influence the release dimensions and thus destructive potential of slab avalanches. In general, it is difficult to determine these parameters concurrently, and most experimental methods are based on first‐order scaling laws that have considerable errors unless very large test specimens are used. Here we introduce a simple experimental method based on a higher‐order quasi‐brittle scaling law that has never been applied to snow nor any other geophysical material. We conducted hundreds of beam bending experiments using natural cohesive snow samples to produce the most comprehensive measurements to date of the tensile fracture toughness and effective process zone length of snow. We also adopt a new penetration resistance gauge to index the fracture toughness data, addressing a longstanding need for better proxy measurements to characterize snow structure. The peak penetration resistance met by a thin blade proved better than the bulk snow density for predicting fracture toughness, a finding that will improve field predictions and facilitate comparisons of results across studies. The tensile fracture process zone, previously a highly uncertain length scale related to avalanche fractures, is shown to be about 5–10 times the snow grain size, implying nonlinear fracture scaling for the majority of avalanches.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".