Analysis on Stability of Subgrade Slope Influenced by Strength Attenuation
Bibliographic record
Abstract
The water content in the subgrade changes easily as the variation of the environment water, which causes the strength attenuation of the subgrade. It is harmful to the stability of subgrade slope. Strength decay pattern of silt soil in yellow river alluvial plain is studied through the laboratory test. And then the finite element software GEO-SLOPE is used to calculate coefficient of stability under different conditions. Results show strength indexes of silt soil are maximum in the optimal water content, and the change of the water content would cause strength attenuation. The stability of subgrade slope decreases as the strength degradation, while the evolution is different, which is semi-parabolic in the lower subgrade but rectilinear in the higher subgrade. Seismic load leads to stress concentrate at the slope, combined with the strength attenuation the landslide is easily to take place.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.010 | 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".