Influence of grass roots on shear strength of pyroclastic soils
Bibliographic record
Abstract
This paper investigates the effects of indigenous vegetation on the shear strength of loose pyroclastic soils of the Campania region (southern Italy); these soils are frequently affected by shallow landslides 1–2 m deep that experience static liquefaction during the post-failure stage. Perennial graminae grasses were seeded in a one-dimensional column 2 m high and filled by pyroclastic soils, allowing the root to grow under atmospheric conditions. A noninvasive sampling procedure was adopted to take the vegetated soil samples, in which the roots were in their natural geometrical distribution. For each rooted sample, the root biomass, RM, was measured and the root volume density, RVD, was calculated. Isotropic consolidated triaxial tests in both drained and undrained conditions were performed on the rooted specimens, as well as on bare specimens as a control. The obtained results showed that the roots generally provided an increment to the soil strength. In drained conditions a reduction in the volumetric deformation was observed, which, under undrained conditions, was reflected in a general reduction of the excess pore-water pressures with a possible inhibition of the static liquefaction occurrence. This study highlights the potential role of grass roots as bio-engineering practice for stabilizing shallow covers of pyroclastic soils.
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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".