Enhancing Soil with Low-Cost Pozzolanic Materials: Rice Husk Ash and Groundnut Shell Ash Compared to Cement
Bibliographic record
Abstract
This study investigates whether low-cost pozzolanic materials such as rice husk ash, groundnut shell ash can improvement soil used in the study that are classified as Lowplasticity clays (cl) and activity of it equal to 1.05 as a replacement for traditional, costly additives.the percentage are used be 4%, 6%, 8%, and 10% of weight soil for each additive.chemical properties were studied for rice husk ash, groundnut shell ash, and cement Portland such as CaO, SiO2, Al2O3, Fe2O3, MgO, K2O, and Na2O.Also, preand post-mixture soil was tested for Atterberg's Limit, Activity, Shrinkage Limit, Clay value, Proctor Standard Compaction, and Unconfined Compressive Strength.Untreated soil samples were compared to treated ones.Adding 8% cement OPC, 10% groundnut shell ash, and 10% rice husk ash enhanced soil cohesiveness from 21 to 57.5, 52, and 45 kPa, respectively, also the optimal soil moisture content dropped from 15% to 8%, 10.5%, and 10% for mixes.Increased mixer percentages lead to reduced maximum dry unit weight and optimized water content.Based on these observations aims to develop effective solutions for treatment expensive soil in engineering and construction projects.
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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 | 0.000 | 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".