A new mathematical model for the estimation of shear modulus for unsaturated compacted soils
Bibliographic record
Abstract
Small-strain shear modulus ( G) is an essential parameter for many geotechnical analyses. Most of shallow foundations are constructed in an unsaturated soil and the shear modulus of the unsaturated soil fluctuates because of the precipitation, evaporation, and rising of ground water table. In this paper, a new mathematical model is proposed for the estimation of the shear modulus function, Gunsat, which defines the relationship between small-strain modulus of unsaturated soil and matric suction. In the proposed model, the soil-water characteristic curve in the form of the degree of saturation is used as the input information. There are additional two parameters named n and C, which can be calibrated with the experimental data, are adopted in the proposed model. The estimated results show good agreement with the experimental data from literature. The proposed method can be used to track the tendency of Gunsat and minimize the data points from the laboratory tests.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".