Soil Cementation Generated and Enhanced by Electrokinetics
Bibliographic record
Abstract
Electrokinetics has been applied in geotechnical engineering, specifically in soil improvement, for nearly a century. Most engineering applications and research projects have focused on electro-osmotic consolidation generated by the negative pore water pressure, as well as settling of suspended soil solids due to electrophoresis. Although many studies have reported that significant cementation bonds have developed in soils after electrokinetic treatment, a systematic study on the subject (i.e. the mechanism and observations from field and lab experiments) has not been reported. In this review, the cementation developed in marine sediments and offshore calcareous sands is presented along with discussion of the principles of electrokinetic cementation. The study is of particular importance in earthquake engineering for development of soil improvement technologies against seismic loading, because electrokinetics generated cementation of soils may significantly reduce the risk of soil liquefaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".