A Modified Oedometer Setup for Simultaneously Measuring Hydromechanical Stress-Strain Paths for Soils in the Unsaturated State
Bibliographic record
Abstract
Abstract This article reports a modified setup for an automatic oedometer apparatus that was designed at the Université de Sherbrooke, Quebec, Canada. The proposed setup can be used to simultaneously measure the superimposed volume change of a soil specimen caused by mechanical loading and suction imposition along with continuous measurement of water exchange. The combined use of air and water volume/pressure controllers allows the operator to use the axis translation technique to impose matric suction. The setup can also be used to carry out the conventional negative water column technique using a single burette or the water volume/pressure controller to apply suction within the range of 0 kPa to 25 kPa under atmospheric air pressure conditions. A modified Tempe cell was designed to ensure the airtightness of the cell and enhance the freedom of the specimens to move vertically during one-dimensional loading and soil-water retention tests, which is particularly of interest for practical cases in which accurate vertical deformation measurement (as low as 0.02 %) is required. Details of the calibration and test procedures are described and discussed. The test results of reconstituted specimens of a fine sand mixture and Ascot Corner silt are also presented to demonstrate the key features of the modified apparatus.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".