Regional-Scale Evaluation of Landslide Distribution and Its Relation to Climate in Southern Alberta, Canada
Bibliographic record
Abstract
This work illustrates a semi-quantitative approach to evaluate changes in regional landslide distribution as a consequence of forecasted climate change, which can be adopted at other regions. We evaluated the relationship between climate conditions and landslide distribution at a regional scale. In this study, landslides on parts of the Battle, Red Deer, and Bow Rivers that are located within the Bearpaw Formation in Southern Alberta, Canada, were mapped, and their characteristics were compared. In order to find a relationship between the climate conditions and the mapped landslides, 30-year annual precipitation and other factors, such as slope aspect and geology, were compared between the river valleys. The results show that climatic conditions and the size and shape of the landslides are different in the Battle River area compared to the Red Deer and Bow Rivers regions. The weak Bearpaw overconsolidated shale and the bentonite layers throughout the region are sensitive to moisture and create favorable conditions for landslides in the river valleys. Further investigations into the long-term impact of climate on the formation of river valleys and the Bearpaw Formation support the argument that climate is one of the main factors in causing variations in landslide distribution across the study areas. These findings provide insight into possible changes in regional landslide distribution as a consequence of climate change.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".