Bibliographic record
Abstract
Vane shear test data obtained by a number of researchers show that the excess pore pressures generated within the soil surrounding the vane by vane insertion and rotation and their effects on the measured vane shear strength have been misinterpreted for many years. The accepted model developed by Blight of field vane testing and the accepted criteria for determining undrained and fully drained vane shear strengths are based on this misinterpretation. Consequently, estimates that are based on this model of the degree of drainage that has been attained at the time the vane shear strength is measured may be significantly in error, and the measured undrained shear strengths may be unconservative. A revision of Blight's approximate theory of field vane testing is presented which is consistent with the available experimental data. Revised practical criteria for determining the undrained and fully drained shear strengths are also presented, and a simple revision of current standard vane shear test methods is proposed which would eliminate, for all but those soils with very high coefficients of consolidation, the possibility that estimates of the undrained vane shear strength may be unconservative.Key words: vane shear, undrained strength, drained strength, excess pore pressure.
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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".