Characteristics, Kinematics and Contributing Factors of Compound and Translational Landslides in the Interior Plains of Canada
Bibliographic record
Abstract
Understanding landslide kinematics, their characteristics, and contributing factors is crucial for decision-making regarding mitigation strategies for infrastructure projects. These characteristics depend on the geomorphology of the area, climate, and proximity to water bodies and anthropogenic activity. Some geomorphological features are shared between some western Canadian regions, particularly within the Canadian Interior Plains (Interior Plains). This paper synthesizes the failure mechanisms, kinematics, triggering events, and contributing factors associated with 11 landslides in the Interior Plains, with detailed qualitative descriptions of two of them. The paper discusses the commonalities of bedrock formations that contain thin sub-horizontal and continuous deposits of weak materials as the main geomorphological predisposing factor for landslides in this region. The findings show commonalities in the effect of seasonal fluctuations in the characteristics of water bodies in contact with these landslides, driving episodes of landside reactivation, acceleration and deceleration. Importantly, anthropogenic activity as a trigger for the initiation of some of these landslides suggests a high susceptibility of certain slopes in the Interior Plains to instability resulting from relatively small changes in in-situ stresses. This information becomes critical for assessing the landslide susceptibility of valley slopes in this region for infrastructure planning, design, and operation.
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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 | 0.003 |
| Science and technology studies | 0.003 | 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".