Magnitude and frequency of landslides triggered by a storm event, Loughborough Inlet, British Columbia
Bibliographic record
Abstract
Abstract. One hundred and one landslides were documented across 370km2 following a rainstorm that swept the British Columbia coastline on 18 November 2001. Despite the regional nature of the storm, the landslides were spaced close together, even within the study area. Landslide clustering is attributed to high intensity storm cells too small to be recorded by the general hydrometric network. The evidence nicely corroborates previous historical studies that reached similar conclusions, but against which there was no modern analog analyzed for coastal British Columbia. Magnitude-cumulative frequency data plotted well on a power law curve for landslides greater than 10000m2, however, below that size several curves would fit. The rollover effect, a point where the data is no longer represented by the power law, therefore occurs at about 1.5 orders of magnitude higher than the smallest landslide. Additional work on Vancouver Island has provided evidence for rollovers at similar values. We propose that the rollover is a manifestation of the physical conditions of landslide occurrence and process uniformity. The data was fit to a double Pareto distribution and P-P plots were generated for several data sets to examine the fit of that model. The double Pareto model describes the bulk of the data well, however, less well at the tails. For small landslides (<650m2) this may still be a product of censoring. Landscape denudation from the storm was averaged over the study area and equal to 2mm of erosion. This is more than an order of magnitude larger than the annual rate of denudation reported by other authors for coastal British Columbia, but substantially less than New Zealand. The number is somewhat affected by the rather arbitrary choice of a study area boundary.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".