ON THE LIQUID LIMIT OF SENSITIVE CLAY
Bibliographic record
Abstract
Quick clays are ubiquitous materials in Sweden, Norway, and Canada. When disturbed, these sensitive clays transform into a liquid, losing all its strength, and cause natural disasters. Both mineralogy and salinity have a major impact on quick clay behaviour. Liquid limit is one of the determining properties for quick clays since the water content in this type of clay is usually higher than the liquid limit. In this study, two different types of commercial kaolinites, and natural Kärra clay were utilised to determine how mineralogy affects the liquid limit. In addition, a 1M NaCl solution was added to the clays to understand the impact of salinity on the liquid limit. The results showed that although the liquid limit for Kärra clay increases with an increase in salinity, adding NaCl solution to kaolinite causes a drop in the liquid limit. Therefore, kaolinite cannot be the determining mineral for the emerging liquid limit of sensitive clay.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".