Enhancing Lime Dosage Determination for Lean Clay Soil Improvement: Significance of Plasticity Limit and Interpretation Approach
Bibliographic record
Abstract
Enhancing the engineering properties of clayey soils is crucial for improving their performance in construction projects. Determining the optimal lime dosage using the Chemical Fixation Point (CFP) concept presents challenges due to soil variability, interactions with chemical and organic components, and limitations in environmental or equipment conditions, especially in pH-based methods. These challenges are exacerbated when non-standard lime or lime residues replace conventional lime. This study highlights the plasticity limit as a key parameter for optimizing lime dosage and assessing treatment effectiveness with lime residues. By analyzing four lean clay soils through CFP tests, plasticity limit measurements, and resistance evaluations, an improved methodology for CFP determination using pH–dosage curves is proposed. The findings validate the feasibility of lime residues, emphasize the plasticity limit’s critical role in lean clay treatment, and extend its relevance to soil stabilization. This work enhances CFP test accuracy and supports sustainable, adaptable soil improvement strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".