Cement Stabilization of Conventional Granular Base and Recycled Crushed Portland Cement Concrete
Bibliographic record
Abstract
Challenges in finding high-quality sources of natural aggregate have led Saskatchewan, Canada, road agencies to explore alternative solutions to meet aggregate demands. The use of recycled materials, such as recycled portland cement concrete (PCC), though traditionally limited to low-quality applications such as subbase or backfill materials, shows promise as a technically viable solution that also offers economic and environmental advantages. In this study, mechanistic material testing was used to examine the effects of cement stabilization on traditional granular base and on two impact-crushed recycled PCC materials from different locations. The unstabilized PCC materials had substantially better mechanistic material properties than the unstabilized conventional granular base material; this result indicates that PCC materials could be suitable for use in high-quality applications, such as base course layers, rather than being limited to use in low-quality applications, such as utility and embankment fills. This study also showed that cement stabilization substantially improved the mechanistic properties of conventional granular base material, yet had a much less pronounced effect on the material properties of the PCC materials. This result may be attributable to poor absorption of the cement by the PCC or a lack of rehydration of the PCC. There was minimal variability in the mechanical behavior of the PCC specimens despite a difference in stockpile location. Both types of PCC material were processed and crushed with the same technique and equipment.
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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 | 0.001 | 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".