Use of the Sharp Cone Test for In Situ Determination of Undrained Shear Strength of Clay
Bibliographic record
Abstract
A recently developed in-situ testing method, called "The Sharp Cone Test" consists in pushing a low-angle truncated cone with 2 degrees taper into a smaller diameter prebored pilot hole. As the cone descends, it causes a continuous enlargement of the pilot hole, which, with a proper instrumentation, can be translated into a relationship between radial pressure and radial (or shear) strain, similarly as in a pressuremeter test. A first, preboring version of the sharp cone with three lateral pressure sensors, was tested in the field five years ago, and yielded positive results (Ladanyi et al. 1995). The present paper describes the use in the field of an improved, self-boring version of this instrument with four total-pressure transducers mounted on its lateral surface at different distances from its lower end. The new probe is able to furnish continuously four points of the pressure-expansion curve, which can be translated into a stress-strain relationship, using conventional pressuremeter data processing procedure. During 1998, the new instrument was tested in a thick layer of saturated clay at a site near Montréal. A comparison of the results with those obtained at the same site by some other types of tests, such as self-boring pressuremeter test and static cone test, was encouraging. The new testing method represents in fact a continuous and automated version of the pressuremeter test.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".