Numerical simulation of the December 4, 2007 landslide-generated tsunami in Chehalis Lake, Canada
Bibliographic record
Abstract
Abstract On December 4, 2007, a three million cubic metres landslide impacted Chehalis Lake, 80 km east of Vancouver, Canada. The failed mass rushed into the lake and parented a tsunami that ran up 38 m on the opposite shore, destroyed trees, roads and campsite facilities. Armed with field surveys and multihigh-tech observations from SONAR, LiDAR and orthophotographs, we apply the newly developed ‘Tsunami Squares’ method to simulate the Chehalis Lake landslide and its generated tsunami. The landslide simulation shows a progressive failure, flow speeds up to ∼60 m s–1, and a slide mass stoppage with uniform repose angle on the lakebed. Tsunami products suggest that landslide velocity and spatial scale influence the initial wave size, while wave energy decay and inundation heights are affected by a combination of distance to the landslide, bathymetry and shoreline orientation relative to the wave direction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".