Field and laboratory behaviour of fine-grained soil stabilized with lime
Bibliographic record
Abstract
Fine-grained soils, due to their high plasticity, possess great shrinkage potential and high compressibility and are responsible for very substantial maintenance costs during the service life of the associated infrastructures. Stabilization of such soils with lime is one of the most effective procedures to mitigate these undesirable characteristics and, at the same time, to enhance their mechanical properties. Current research seeks, through field and laboratory tests, to quantify the influence of calcitic hydrated lime on the strength and deflection characteristics clayey soil from the Paraguayan region of Chaco. The influence of different dry unit weights, lime amounts, and curing periods on the strength and deflection of a Paraguayan clay stabilized with lime was assessed. The present work shows, for the first time ever, that the porosity/lime index is the proper parameter to be used in the field when dealing with the strength of clay–lime bases of pavements. Hence, the results presented herein are a contribution to understanding the conditions in which these soils can be stabilized to be used in infrastructural applications.
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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 | 0.000 | 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) | 0.001 | 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".