Sediment transfer by shallow landsliding in the Queen Charlotte Islands, British Columbia
Bibliographic record
Abstract
Despite the importance of landsliding in routing sediment through mountainous drainage basins, few studies have documented landsliding rates over extended time and space scales. We have investigated landsliding in surficial material in the Queen Charlotte Islands using a large inventory of events, derived from aerial photography, covering an area of 166.7 km2. The mean erosion rate for shallow landsliding is 0.10 mm·a1, which is at the upper end of shallow landsliding rates observed in the Pacific Northwest and coastal British Columbia, but several orders of magnitude lower than rock-based landsliding rates reported in the literature. Probability distributions for landslide area and volume are somewhat convex in form. Flattening of the curve found at low magnitudes may be due to sampling bias or physical mechanisms inhibiting failure, and the steepening for high values may exist because the sampling period is not long enough to adequately represent large events. Landslides generally initiate on hillslope gradients greater than 0.500.60. The largest numbers of landslides occur on south- to southwest-facing slopes and east- to northeast-facing slopes. Most events occur on concave and straight hillslopes in upper-slope positions. Landsliding rates were found not to be affected by rock type. Hillslopes in the Queen Charlotte Islands are often mantled by weathered Quaternary deposits and, hence, landsliding events are not directly controlled by weathering of bedrock. About 31% of landslides identified in this study deposited material in stream reaches, with about 83% of these landslides deposited in reaches with gradients between 3% and 10%.
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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 | 0.002 |
| 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) | 0.002 | 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".