Experimental and Optimization Study on the Sliding Force Monitoring and Early Warning System for High and Steep Slopes
Bibliographic record
Abstract
A series of high and steep slopes have been formed due to the deep exploitation of resources in open‐pit mines across China. The stability of these high and steep slopes has become an essential factor affecting the efficient, safe, and sustainable development of deep mineral resources. Due to numerous problems such as constant resistance fluctuation and pipe jamming of the original sliding force monitoring system, leading to system failure, a series of improvements on the current monitoring systems were implemented. This specific work included a mechanical characteristics test of the anchor cable, improvement of the constant resistance structure, and measurement of the internal displacement of the slope. The communication mode and the software architecture of the system were also adjusted. This work significantly improved the overall performance of the sliding force monitoring and early warning system. The improvements performed in this research are systematically described to provide an example of good practice for other sites with similar features. The collected data show that the improved sliding force monitoring system can accurately reflect the whole process of landslide incubation. Moreover, the validity of the early warning criterion based on the sliding force is verified again using the field test.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".