Influence of Lateral Erosion Depth in Basal Sand Layer on Failure Mode of Jiaohe Ruins Cliff
Bibliographic record
Abstract
This paper presents basal friction tests to simulate the influence on the deformation and the failure modes in Jiaohe Ruins cliff due to increasing erosion in the basal sand layer. Previous research, including field investigation, physical testing and wind tunnel tests, has proved there are different scales of wind erosion in Jiaohe Ruins Cliff. A scaled cliff model is established with existing secondary unloading fissures scaled accordingly. A test set-up is used with a rotating platform to rub the model in order to simulate the gravity on the cliff. The influence of soil erosion depth is investigated by comparing the results from models with different erosion depths. Based on the results, it is found that the scaled model tests can be used to simulate the failure mode of the cliff. The cliff failure mode changes from fracturing-toppling to shearing-dropping with increasing basal erosion depth. When the sand layer is partially eroded, the silty clay cliff topples and falls along the unloading fissures due to gravity moment. When the sand layer is fully eroded, the cliff block falls in a shearing mode along the fissures. This research improves the understanding of the failure in Jiaohe Ruins cliff and provides a scientific reference for the reinforcement of this historical site.
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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 | 0.000 | 0.000 |
| 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".