Effects of sampling in soft clay: a microstructural insight
Bibliographic record
Abstract
This paper analyses the effects of tube sampling in soft clay with particular emphasis on the modifications that occur in the clay fabric for tube specimens retrieved using open samplers (Shelby) as well as a fixed-piston sampler. Tube specimens of an estuarine soft clay retrieved from the National Soft Soil Testing Facility located at Ballina in northern New South Wales (Australia) are analysed in this study. Mercury intrusion porosimetry tests are carried out to infer the pore size density function of specimens trimmed at different locations along the tube and these are compared against those performed on undisturbed clay, obtained from Sherbrooke specimens, to estimate variations in the natural soil fabric due to tube sampling. It is shown that tube sampling induces important modifications in the natural pore size distribution (PSD) of the clay, not only at the perimeter but also at the centreline of the sampler. This phenomenon is more pronounced at the top and bottom ends of the sampler and increases with a decrease in the sampler diameter. The use of the large-diameter fixed-piston sampler reduces dramatically the variations in both the micro and macro void ratios during tube sampling.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".