Discussion of “Analysis of the internal stability of granular soils using different methods”
Bibliographic record
Abstract
Moraci et al (2014) presented a good paperwith interesting ideas on the assessment of internal stability against suffusion of soils. The discussers offer some simple notes related to the method proposed in the paper. There are many methods in the literature to assess internal stability, including (among others) Kenney and Lau (1985, 1986), Burenkova (1993),Wan and Fell (2008), andDallo et al. (2013). All of them contain some percentage of error in predicting the internal stability of soils. It is very interesting to note that the proposed butterfly-wings chart in the paper under discussion contains two zones where the soil is classified as definitely stable and unstable. To further validate this classification, we have analyzedmore data in the literature. In total 31 laboratory tests have been reanalyzed. These data were obtained from the tests of Wan and Fell (2004, 2008) (14 test samples); Skempton and Brogan (1994) (four test samples); Kenney and Lau (1985) (12 test samples); and Sadaghiani and Witt (2011) (one test sample). The grain-size distributions (GSD) are shown in Fig. D1a for internally stable soils and in Fig. D1b for internally unstable soils. These GSDs are reanalyzed according to the butterfly-wings method and the results are shown in Fig. D2. As can be seen, all of the internally stable soils are located in the internally unstable zone, except for soils “Ds” and “23” tested by Kenney and Lau (1985). Soil “Ds” is located in the uncertain zone A, while soil “23” is located on the borderline between the unstable zone and uncertain zone B. Our results in Fig. D2 clearly show that the butterfly-wings method tends to be conservative in evaluating internal stability of soils. In Fig. D2, the value of F represents the average value of F1 and F2, as suggested by the authors, where F1 is the finer percent corresponding to (H/F)min as computed from the Kenney and Lau (1985) method, and F2 is the finer percent corresponding to (D15 coarse/D85 fine)max as computed from the Kezdi (1969) and Sherard (1979) methods. The aim of the authors’ suggestion is to consider one value of F for the three different methods. This suggestion is valid as long as the difference between F1 and F2 is small. The 31 grading curves analyzed by the discussers show a considerable difference between the values of F1 and F2 as shown in Fig. D3. The discussers believe that this difference is the fundamental reason for the less successful application of the proposed butterfly-wings method to the soils we analyzed.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".