Structural analysis of Turtle Mountain: origin and influence of fractures in the development of rock slope failures
Bibliographic record
Abstract
Abstract Large slope failures in fractured rocks are often controlled by the combination of pre-existing tectonic fracturing and brittle failure propagation in the intact rock mass during the pre-failure phase. This study focuses on the influence of fold-related fractures and of post-folding fractures on slope instabilities with emphasis on Turtle Mountain, located in SW Alberta (Canada). The structural features of Turtle Mountain, especially to the south of the 1903 Frank Slide, were investigated using a high-resolution digital elevation model combined with a detailed field survey. These investigations allowed the identification of six main discontinuity sets influencing the slope instability and surface morphology. According to the different deformation phases affecting the area, the potential origin of the detected fractures was assessed. Three discontinuity sets are correlated with the folding phase and the others with post-folding movements. In order to characterize the rock mass quality in the different portions of the Turtle Mountain anticline, the geological strength index (GSI) has been estimated. The GSI results show a decrease in rock mass quality approaching the fold hinge area due to higher fracture persistence and higher weathering. These observations allow us to propose a model for the potential failure mechanisms related to fold structures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".