The propagation saw test: slope scale validation and alternative test methods
Bibliographic record
Abstract
Abstract The propagation saw test (PST) is a recently developed snowpack test that enables assessment of the fracture propagation propensity of selected persistent weak-layer and slab combinations, which are known to release dry-slab avalanches. In this paper, we assess the slope- scale accuracy of the standard PST method at validated sites of observed weak-layer fracture initiation, with or without propagation. We also report on experiments with alternative test methods and varying saw thicknesses. Results show the standard PST method is comparably accurate to other common snowpack tests in predictive skill when predicting propagation propensity on the slope scale. Although a slight but significant dependence on saw thickness was found, it did not affect the interpretation in our validation study. Alternative methods such as scaling the test column length with weak-layer depth or leaving the upslope end of the column attached to the surrounding snowpack did not improve slope- scale accuracy and these tests were often more difficult to interpret.
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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 | 0.001 | 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 | 0.000 |
| 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".