Effects of waste glass additions on the properties and durability of fired clay brickThis article is one of a selection of papers published in this Special Issue on Masonry.
Bibliographic record
Abstract
The optimization of the production of fired clay brick is essential for the sustainability of the clay brick industry. While there exist areas for improvement of these bricks’ properties when they are used in severe climates, concerns — including nonrenewable resource depletion, increasing energy costs, and waste management — have become increasingly important in Canadian and global industries. One strategy to address these concerns is to use waste additives as fluxing agents in bricks. Use of these additives can decrease the dependency of the industry on nonrenewable resources and can improve brick strength and durability. The effect nonrecycled waste glass additives have on fired brick durability and mechanical and transport properties was investigated in this study. The variables studied were waste glass particle size and percentage added by mass. Microstructure was investigated using mercury intrusion porosimetry to determine the effect on pore structure. The results yielded an optimal percentage addition of waste glass.
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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 | 0.000 |
| 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".