Assessment of engineering properties of Bangkok clay
Bibliographic record
Abstract
Due to the effect of structure, Bangkok clay is stable in a metastable state. Its void ratio, e, is the summation of the void ratio sustained by the intrinsic fabric, eR, and the additional void ratio due to the structure, es. The intrinsic state line (eRversus log σ′v, where σ′vis the effective vertical stress) is developed in terms of the void ratio at the liquid limit, eL. At the post-yield state, esis inversely proportional to σ′v. The residual additional void ratio, esr, which cannot be eliminated by the increase in effective vertical stress, is constant at about 0.20 for soft Bangkok clay and 0.12 for medium stiff Bangkok clay. From these findings and the ideal condition of zero compression at the pre-yield state, the field yield stress and field compression curve can be assessed. The undrained shear strength is directly related to the field yield stress, since both reflect the structure. The soil structure does not significantly influence the permeability. The permeability of the clay in structured and destructured states is identical under the same void ratio and can be determined from the generalized state parameter, e/eL. These observations result in a simple and practical method for assessment of the engineering properties of natural Bangkok clay.Key words: Bangkok clay, destructured state, compression, intrinsic state line, permeability, structured state, vane shear strength.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".