Protocol for the assessment of unsaturated soil properties in geotechnical engineering practice
Bibliographic record
Abstract
The implementation of unsaturated soil mechanics into routine geotechnical engineering practice requires an evaluation of methodologies that may be used for the assessment of “unsaturated soil property functions.” Guidelines and recommendations need to be provided to practicing engineers. The guidelines need to take the form of “engineering protocols” that define acceptable standards for engineering practice. “Engineering protocols” for unsaturated soils engineering practice can be divided into “preliminary design” protocols and “final design” protocols. Both design levels involve the use of a variety of estimation procedures that have been proposed for various classes of geotechnical problems (e.g., unsaturated flow, shear strength, volume change, and distortion). The hierarchy in methodologies is based mainly on the costs and risks associated with a particular engineering project. In this paper, “hierarchical levels” are suggested that take into consideration the cost of various direct and indirect methodologies for the determination of unsaturated soil properties. Recommendations and suggestions are provided for methods for the determination and use of the soil-water characteristic curves (SWCC) and consequently, for the computation of unsaturated soil property functions (USPFs). Primary attention is given to estimation procedures best known to the authors and most appropriate for geotechnical engineering practice.
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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 | 0.118 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.038 | 0.031 |
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".