The Importance of Rock Mass Damage in the Kinematics of Landslides
Bibliographic record
Abstract
The stability and kinematics of rock slopes are widely considered to be functions of lithological, structural, and environmental features. Conversely, slope damage features are often overlooked and considered as byproducts of slope deformation. This paper analyzes and discusses the potential role of slope damage, its time-dependent nature, and its control on both the stability of rock slopes and their kinematics. The analysis of several major landslides and unstable slopes, combined with a literature survey, shows that slope damage can play an important role in controlling short- and long-term slope stability. Seasonal and continuously active events cause permanent deformation within the slope due to the accumulation of slope damage features, including rock mass dilation and intact rock fracturing. Rock mass quality, lithology, and scale control the characteristics and complexity of slope damage, as well as the failure mechanism. The authors propose that the role of slope damage in slope kinematics should always be considered in slope stability analysis, and that an integrated characterization–monitoring–numerical modelling approach can enhance our understanding of slope damage, its evolution, and the controlling factors. Finally, it is emphasized that there is currently a lack of guidelines or frameworks for the quantitative assessment and classification of slope damage, which requires a multidisciplinary approach combining rock mechanics, geomorphology, engineering geology, remote sensing, and geophysics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".