Experimental and Theoretical Study to Evaluate the Previous Studies for Expansive Soils
Bibliographic record
Abstract
Expansive soils, characterized by their propensity to undergo volume changes in response to moisture variations, pose significant challenges to civil engineering due to the presence of the montmorillonite mineral.This mineral exhibits a high capacity for water absorption, leading to volumetric expansion and consequent soil heave.This study aims to provide a comprehensive understanding of the behavior of expansive soils, focusing on variations induced by different proportions of bentonite enrichment.In this research, both experimental and theoretical approaches are employed.Experimentally, the swell percentage, liquid limit, plastic limit, shrinkage limit, maximum dry density, and optimum moisture content are determined for three bentonite-enriched soil samples: clay with 40%, 60%, and 80% bentonite.Theoretically, the validity of existing empirical equations is assessed in light of the experimentally observed behavior of the bentonite-enriched soils.This dual approach allows for a nuanced understanding of the behavior of expansive soils and provides a foundation for the development of more accurate predictive models.Through this integrated analysis, this study contributes to the body of knowledge on the impact of expansive soils on civil engineering structures and offers a pathway towards more effective management of these challenges.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".