Analysis of the internal stability of granular soils using different methods
Bibliographic record
Abstract
The knowledge of the internal stability of granular soils is a key factor in the design of granular or geotextile filters. To evaluate the internal stability of granular soils, different semi-empirical methods are generally used. Nevertheless, the results of these methods, on the same soil, can lead to different internal stability evaluations. In this paper, to evaluate the reliability of the semi-empirical methods available in literature, the internal stability of different granular soils, reconstituted by the authors and by other researchers, has been studied by means of theoretical and experimental approaches. In particular, the theoretical analysis of the internal stability was performed using the Simulfiltr method, developed recently by the authors, while the experimental evaluation of the internal stability was carried out by means of long-term filtration tests. The comparison of the internal stability analysis performed by means of semi-empirical, theoretical, and experimental methods showed that the semi-empirical methods are not always reliable. Therefore, on the base of these results, a new chart, in terms of minimum slope Smin (%) of the grain-size distribution and of average value of finer percentage F, has been proposed to evaluate the internal stability of granular 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".