Evaluating debris slide occurrence using digital data: paraglacial activity in Chilliwack Valley, British Columbia
Bibliographic record
Abstract
Debris sliding is one of the most important processes acting to transport sediment within mountainous regions. Detailed study of debris slide activity at the basin scale typically involves landslide inventories generated from aerial photographs. However, it has been shown that some types of rapid mass movement can be accurately identified using a combination of high-resolution satellite imagery and digital elevation data. This approach is beneficial as the digital products allow for a more accurate and efficient data throughput into various types of geomorphic analysis. Here, we demonstrate the use of an automated inventory in the geomorphometric evaluation of debris slide initiation for the Chilliwack Basin, British Columbia, Canada. Our results indicate that the occurrence of debris sliding is primarily determined by topographical controls. For basins that are in equilibrium with the existing climate, the frequency of debris sliding should demonstrate a strong relationship to bedrock geology as the production of unconsolidated materials available for failure is a function of weathering rates under these conditions. The lack of bedrock control within the Chilliwack Basin suggests a state of paraglacial relaxation, wherein glacial deposits dominate the sediment cascade within the area. Therefore, topographic parameters can be used to discriminate the location of metastable slopes where debris slide erosion will be active. The use of digital data in the characterization of debris slide occurrence would seem to be a viable alternative to the more traditional methods.
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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 | 0.003 | 0.005 |
| 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) | 0.002 | 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".