Comparing Fracture Propagation Tests and Relating Test Results to Snowpack Characteristics
Bibliographic record
Abstract
ABSTRACT: The Propagation Saw Test (PST) and the Extended Column Test (ECT) are two recently and independently developed field tests that indicate the propensity for a slab and weak layer combination to propagate a fracture. University of Calgary researchers performed the PST and ECT throughout the 2008 winter season along with other standard stability tests to establish their strengths and limitations. The PST and ECT were compared side-by-side in over 80 test pits with close to 600 individual test results throughout the 2008 winter in the Columbia Mountains of British Columbia, Canada. We tested numerous slab and weak layer combinations including tracking four persistent weak layers from initial burial to depths of over two meters. Field observations and initial analysis indicate correlations between slab hardness, weak layer depth, and propagation propensity, and hint at how these snowpack characteristics influence the observed results of each test. We discuss the specific slab and weak layer combinations that appear to have high, low, or no propagation propensity, and suggest particular conditions under which one test is more appropriate than the other for aiding forecasters in assessing propagation propensity.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".