In situ measurement of root reinforcement using corkscrew extraction method
Bibliographic record
Abstract
Mechanical root reinforcement is an important parameter to evaluate for stability analysis of rooted slopes. The contribution of roots is however difficult to quantify in situ without time-consuming methods or heavy equipment. Here we report field testing using the newly developed “corkscrew” method at two different sites with plantings of conifers and blackcurrant. In both sites we found positive correlations between root quantity and root reinforcement in surface layers where many roots were found. Below 125 mm depth, no correlations could be found, probably due to variability in soil stress and gravel content. Roots were shown not only to increase the soil peak strength, but also to add ductility to the soil, i.e., adding strength over much larger displacement ranges. Measured reinforcement, although similar to other experimental studies, was smaller than predicted using existing models. This may be attributed to the distinct difference in shear displacement required to mobilize the strength of rooted soil as compared with fallow soil. At displacements sufficient to mobilize root strength, the soil strength component has reduced from peak to a much smaller residual strength. The corkscrew method proved a promising tool to quantify root reinforcement in field conditions due to its ease of use and short test duration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".