Sustainable application of recycled plastics in asphalt pavement: case study of a trial in Newtonville, Ontario, Canada
Bibliographic record
Abstract
Global research on using plastic waste in asphalt roads highlights its benefits: recycling waste, reducing greenhouse gas emissions, and providing an alternative to non-renewable asphalt binders. This study aims to bridge the gap between laboratory results and field performance of recycled plastic-modified asphalt in cold regions, promoting broader adoption. Laboratory analysis of core samples was performed as part of a quality assurance program. High-temperature rutting resistance was evaluated using the Hamburg wheel tracking test, while low-temperature cracking resistance was assessed through semi-circular bending testing. Results show that the impact of recycled plastics and fibers on rutting resistance varies with temperature, with the greatest benefit at the highest temperatures. For low-temperature cracking resistance, polyethylene terephthalate fibers outperform mixed plastics by delaying crack propagation. Low-temperature conditioning can induce thermal shrinkage in the asphalt mixture, slightly moderating the effects of recycled plastics and fibers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".