Effect of curing conditions on the compressive strength of sodium carbonate activated slag–glass powder mortar
Bibliographic record
Abstract
This study presents the experimental investigation of the effect of curing conditions on the properties of mortar mixtures made with sodium carbonate activated slag–glass powder as a binder. Slag and glass powder were used at an equal percentage as the aluminosilicate precursor and the binary blend was activated with sodium carbonate. The corresponding compressive strength and ultrasonic pulse velocity of the mixtures cured in different conditions were investigated. The curing conditions used in this study are dry, moist, and submerged curing. Microstructural investigations were also carried out to understand the microstructural properties of the mixtures exposed to these curing conditions. Results from this study showed that moist curing is the most effective curing method for mortar made with sodium carbonate alkali-activated slag–glass powder as a binder. Microstructural evaluations further confirm the strength results as mortar samples cured in a moist condition exhibited a denser microstructure.
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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 | 0.001 |
| 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".