Risk-informed design of debris-flow mitigation at Cheekeye Fan
Bibliographic record
Abstract
The Cheekeye Fan, located within the District of Squamish, is prone to debris-flow hazards that pose unacceptable risk to development. This article describes how a debris-flow barrier that would protect existing and proposed development was designed to achieve locally adopted risk tolerance criteria. A risk assessment showed that the barrier should manage debris flows with volumes up to 2.8 Mm3 (1:10 000-year return-period events) to achieve tolerable risk, and that debris flows with volumes below 0.2 Mm3 (10–30-year events) can pass the barrier through an outlet without exceeding risk tolerance thresholds. The local government specifies that tolerable debris-flow risks be reduced “as low as reasonably practicable” (ALARP), defined in this project as the point where the cost of additional mitigation measures is grossly disproportionate to the benefits gained. By estimating the disproportionality ratio for potential auxiliary measures, this study shows that the barrier reduces risk ALARP without additional measures in place. The authors believe that new development approval on Cheekeye fan would not be possible without the risk-informed decision-making process described in this article.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".