Study on the Effect of Root Density on the Shear Strength of Root-Soil Composite: A Case Study of Cynodon Dactylon
Bibliographic record
Abstract
Since the Belt and Road Initiative was proposed, many slopes with poor stability have been formed in China's highway and railway infrastructure construction. In response to the national goals set during the 14th Five-Year Plan to strengthen the ecological security barrier and protect biodiversity, and in line with the philosophy that "lucid waters and lush mountains are invaluable assets," ecological protection technology has been widely applied in slope protection. However, current research and design have not considered the role of roots in retaining walls. This study uses an eco-friendly reinforced soil retaining wall project as an example to investigate the relationship between root density and the cohesion and internal friction angle of root-soil composites through direct shear tests. The results show that increasing root density significantly improves the cohesion and internal friction angle of root-soil composites. When the root density is 5%, the cohesion and internal friction angle increased by 40.57% and 51.41%, respectively, compared to the unreinforced soil sample, providing a theoretical reference for engineering design.
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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".