Verification of the Fredlund (2019) Unsaturated Shear Strength Function
Bibliographic record
Abstract
There has been a proliferation of equations proposed to describe the unsaturated shear strength envelope going back to the 1970s. However, there have been limited studies to verify the suitability of one unsaturated shear strength equation over another. Most proposed shear strength equations have attempted to relate the shear strength of an unsaturated soil to some aspect(s) of the soil–water characteristic curve (SWCC). Estimation procedures have generally focused on using that of air-entry value (AEV) as defined by the drying (or desorption) branch of the degree of saturation SWCC (S-SWCC). This paper studies the suitability of using two “anchor points” (or reference points) along the drying S-SWCC to estimate the unsaturated soil shear strength function. The anchor points referred to are the air-entry value (AEV) of the soil and the “residual suction point” of the soil defined in terms of the S-SWCC. Shear strength conditions associated with both so-called anchor points are used as “boundary conditions” that should be satisfied when estimating the shear strength function for unsaturated soils. Past research laboratory measurements published in the research literature are used as part of the verification process for this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".