Bibliographic record
Abstract
The stability of high rock slopes is controlled by many geological factors including the orientation, size, and location of geological structures, lithology, rock mass strength, hydrogeological setting, and slope topography. Together, these “inherited” factors often control the location, the extent, and the volume of the potential rock mass involved in a rock slope failure. Rock slopes can remain stable for many thousands of years before a de-stabilizing event or “trigger”, causes the slope to fail. However, often the failure of a rock slope is the final outcome of a slow and progressive degradation of the rock mass causing a gradual reduction in slope stability. Many authors have investigated the role of so-called “exogenic” and “endogenic” factors on the evolution of rock slope stability. Exogenic factors may lead to damage in the rock mass at the surface of rock slopes (i.e. weathering, erosion, etc.). Conversely, endogenic factors cause the weakening of the rock mass from within the Earth’s crust (earthquakes, volcanism, etc.). The action of the above factors, extending over thousands of years, and the interaction with the aforementioned inherited factors, causes the formation of rock slope damage features such as tension cracks, rock mass dilation and brittle fracture resulting in “progressive failure” of the slope. In the course of this research, several landslide sites were visited, both in North America (the Downie Slide and the Hope Slide, British Columbia, Canada) and Italy (San Leo landslide). At each site, slope damage was investigated using an integrated remote sensing and numerical modelling approach. It was noted that the accumulation of slope damage was driven and controlled by a complex interaction of factors and geomorphic processes, including glacial and fluvial erosion, steepening and undermining of the slope, debuttressing, slope deformations and fatigue. In this paper we provide clear evidence of how mapping and characterization of slope damage features using state-of-the-art remote sensing methods can provide new insights on the style of slope deformation and the factors that control the stability and failure of rock slopes. Finally, it is recommended that the analysis of rock slope damage should be an important component in the workflow to ensure comprehensive rock slope characterization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".