Mini-block sampler
Bibliographic record
Abstract
Challenges in obtaining high quality samples of sensitive low-plasticity clay in an effective manner have been overcome by the development of the mini-block sampler. The starting point for the development of the new sampler was the Sherbrooke block sampler that was first introduced in Canada in 1979. Although the Sherbrooke block sampler can produce high quality samples, its use, particularly in industrial projects, has been limited due to the perceived high costs, practical difficulties, and the time required. This paper outlines details of the development and design of the mini-block sampler together with developed techniques for protection and transportation of the samples and preparation of specimens for laboratory testing. The sampler has been used successfully at five Norwegian clay sites. For two of the sites comparative Sherbrooke samples were available and it is shown that the quality of the mini-block samples is very high and is at least as good as that of the Sherbrooke samples. The work also demonstrates that rigging, preparation, and sampling with the mini-block sampler is fast, practical and is not labour intensive. Furthermore the resulting samples are easy to transport and handle, but still provide sufficient material for extensive laboratory testing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.018 |
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".