Effect of zeolitization on physicochemico-mineralogical and geotechnical properties of lagoon ash
Bibliographic record
Abstract
A common method to dispose of ash generated from coal-fired thermal power plants is to mix the ash with water and place the ashwater slurry in ponds or lagoons. Such a disposal system allows for the ashwater interaction. Alkalis present in the ash react with water, leading to zeolitization of the ash and changes in its overall properties. To simulate such interaction, controlled experiments have been conducted on a typical Indian lagoon ash, and the effect of zeolitization on the physicochemicomineralogical properties has been studied. The effect of zeolitization on the geotechnical properties of the ash has also been investigated in detail. It is believed that such investigations are essential for bulk utilization of the lagoon ash, particularly as a fill material, where properties like compaction, consolidation, and hydraulic conductivity are very important.Key words: lagoon ash, physical properties, chemical composition, mineralogy, geotechnical characteristics, zeolitization.
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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) | 0.002 | 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".