Cement Stabilization of Conventional Granular Base and Recycled Crushed Portland Cement Concrete
Bibliographic record
Abstract
The performance of typical thin flexible pavement systems depends on the quality of the granular base course. The granular base is responsible for mitigating strains on the subgrade, preventing fines pumping, and managing drainage. Field conditions including high water tables, increased precipitation, and poor subgrade conditions often lead to water pumping and fines migration into granular bases in urban areas. Furthermore, current construction practices favor the use of granular base materials with fines contents at the high end of the base course specifications, as higher fines base courses are thought to be more easily compacted. Additionally, the use of recycled materials is becoming more common, with the natural aggregate source depletion and waste reduction measures in many urban areas. This study examined the effects of increasing fines contents on a conventional City of Saskatoon (COS) granular base material as well as an impact-crushed recycled Portland cement concrete (PCC) aggregate. Gyratory compaction and rapid triaxial frequency sweep characterization were performed on samples with varying fines contents. The results of this study showed that increasing the fines content of the conventional COS granular base improved its compactibility. However, increasing the fines content of the PCC granular base material did not offer substantial improvements in compaction behavior. The mechanistic material results showed that the increased fines contents lessened the mechanistic material stiffness properties of both materials, although the effects of increased fines were often less pronounced with the PCC material.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".