Strength Control Factors of Chlorite Schist under Schistose Structure
Bibliographic record
Abstract
In tunnel engineering, it is important to understand the influence of schistose structure on the failure strength of chlorite schist. To explore the strength control factors of chlorite schist, this paper firstly analyzes the mineral composition and meso structure of chlorite schist of different weathering states. The results show that the mineral composition of chlorite schist is changed during the weathering process, and that chlorite is an anisotropic rock mass. Next, a series of uniaxial compressive tests were conducted on chlorite schist samples with different bedding angles (the angle between bedding plane and loading direction; θ=0°, 15°, 30°, 45°, 60°, 75°, and 90°), moisture conditions (dry and saturated), and weathering states (strongly weathered and weakly weathered). Based on the test data, the authors discussed the change laws of the rock strength with bedding angle, weathering state, and moisture condition. The main results are as follows: Chlorite schist is a low-anisotropy rock mass, whose compressive strength exhibited a V-shaped trend with the growing bedding angle; the schistose structure is the internal cause of the deformation and the anisotropic or transversely isotropic strength of the schist; the schistose structure is reshaped and further damaged by external factors (e.g. water softening and weathering effects) in engineering. The research findings help to improve the rock stability and support design in tunnel engineering.
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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 | 0.000 |
| 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".