Some observations considering undrained shear strength, liquidity index, and fluid/solid ratio of mono-mineralic clays with water–ethanol mixtures
Bibliographic record
Abstract
The mechanical properties of clays are influenced by the characteristics of the fluid in the pore space. The liquid limit reacts differently to the permittivity, ε, of the fluid: for smectites the slopes are positive, for kaolinite and illite they are negative and smaller. This dissimilarity can be explained by the structural differences between swelling smectites with solvated interlayer cations and nonswelling clay minerals such as kaolinite and illite. Undrained shear strengths, cu, of Ca–smectite, but not Na–smectite, correlate with the actual fluid ratio. Regressing cu against the liquidity index, IL, yields two different regression lines for Na–smectite and Ca–smectite. For the first time it is shown that normalizing cu to the ε of the pore fluid results in a single regression line for both smectitic clay types. As kaolinites and illites possess significantly less exchangeable cations than smectites, this yields significantly smaller ranges for Atterberg limits and reduces the impact of ε on almost pure particle–particle interactions. In addition, the much larger particle sizes of the kaolinite and illite may dominate the undrained shear strengths, as normalization of cu to ε did not change the relationship to either the actual water content or the liquidity index.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".