Longevity of dams from landslides with sub-channel rupture surfaces, Peace River region, Canada
Bibliographic record
Abstract
We examined seven landslide dams and their changes over time in the Peace River region of Canada. These landslides had subchannel rupture surfaces in glacial and glaciolacustrine sediments. We assessed the stability of the dams using 6 separate, morphometric-based stability indices (with a total of 10 stability thresholds). The landslides caused the streambeds to be elevated from 4 to 30 m forming the dams. The landslide lakes diminished in size over one to several years through stream incision into the dams and sediment infilling. The longest-lived dam persisted for up to 20 years. For two dams, incision into the dams lowered the lake levels by about half of the total depth, while the remainder of the water in the basins was displaced by sediment infilling. After the lakes drain, the sediment accumulations behind the dams can persist for decades. The stability analyses overpredicted unstable conditions which is inconsistent with the observed longterm persistence of the dams. The landslide dams in our study were relatively stable. Their lakes persisted for up to 2 decades and diminished over time through a combination of slow incision and basin infilling. The stability indices we assessed overpredicted unstable conditions and thus would require modification for these particular types of dams in this regional setting.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".