Experimental Study of Suction Stress Characteristic Framework for Granular Materials Using Conventional Direct Shear Test
Bibliographic record
Abstract
Suction stress characteristic framework is considered as a practical approach to model the state of stress in granular and cohesive soils as a function of degree of saturation or water content. As an important part of effective stress in unsaturated soils, suction stress can be defined by the suction stress characteristic curve (SSCC). Although the SSCC can be directly determined from shear strength tests, studies suggest that it is intertwined with the soil water retention curve (SWRC). In this paper, the conventional direct shear tests along with water retention tests were used to determine the SSCC of fine sand mixture, over a range of suction controlled by water content. The suction stress approach was examined in conjunction with the semi-empirical procedure of predicting unsaturated shear strength by SWRC. The results indicated that conventional shear strength testing approaches along with SWRC models can be effectively used to assess the unsaturated shear strength and effective stress framework.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".