Stabilisation of Clay with Fly-Ash Geopolymer Incorporating GGBFS
Bibliographic record
Abstract
Low water/binder ratio and higher activator content can help to accelerate the setting and strength development of fly-ash geopolymers cured at ambient condition. This study aims to achieve clay stabilization with fly-ash based geopolymer incorporating ground granulated blast-furnace slag (GGBFS), to enhance soil strength performance at ambient temperature. Laboratory experiments were performed on clay samples stabilized with both slag and fly-ash geopolymer and ordinary Portland cement (OPC), including the soil plasticity, compaction and unconfined compressive strength. The investigation was expanded to include un-activated fly-ash/slag clay samples used as control mixtures. The results indicated that introducing GGBFS to class (F) fly-ash based geopolymer assists, when synthesised in certain concentrations, in achieving a setting time and compressive strength comparable to OPC stabilised clay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".