Effects of hydraulic shear stress and rate of erosion on the magnitude, degree, and rate of collapse
Bibliographic record
Abstract
Arid regions worldwide are plagued by collapsible soils. Collapsible soil is characterised by the sudden decrease in volume that occurs when it is subjected to inundation under constant stress. This volume change manifest itself as drastic and unpredicted foundation settlement, which may lead to further catastrophic failure of the supported structures. Collapse settlement is the term applied to the additional settlement of a foundation due to wetting of the underlying soils. The results of an experimental investigation of the effects of the saturation of soil with water, kerosene, and crude oil, and of the effects of the fluid head on the magnitude, degree, and rate of collapse of the underlying soil are presented in this paper. Soil erodibility is presented in terms of the applied hydraulic shear stress and the rate of erosion. The relationship between soil erosion and the magnitude and rate of collapse is examined. Empirical methods for the prediction of the magnitude and rate of collapse of a soil saturated with the test fluids and subjected to a hydraulic constant head are proposed.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".