Mechanical improvement and vertical yield stress prediction of clayey soils from eastern Canada treated with lime or cement
Bibliographic record
Abstract
The method of soil stabilization is well known and has been used throughout the world for many decades to improve some soil properties. Although many researchers have studied the effect of adding a cementing agent to a soil, not many of these researchers have explored the effect of treatment on the resulting properties of high water content soils like dredged material. Also, there has been little work concerning the prediction of the mechanical changes to the soil. Therefore, this paper summarizes the results of a research project conducted to define the general mechanical behavior of high water content clayey soils from eastern Canada treated with lime or cement, in terms of compressibility. In the light of this research, the general compressibility behavior has been obtained, defined by relationships between initial void ratio, additive content, and vertical yield stress for a given inorganic or organic soil. These relationships have been normalized on the basis of the one-dimensional compression curve of the remolded and reconstituted untreated soil to give a simple method for predicting the vertical yield stress of a treated soil for any initial void ratio and its resistance to compression.Key words: stabilization, compressibility, yield stress, clayey soils, lime, cement.
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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 | 0.000 |
| 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".