Low Temperature Performance of Superpave Recycled Hot Mixtures in Ontario
Bibliographic record
Abstract
One of the effects of climate change is the drop in the extreme temperature during winter season. The impact that this phenomenon has on pavement performance is a concern, especially for the Hot Mix Asphalt (HMA) surface layers. The increasing use of sustainable techniques, like the addition of Reclaimed Asphalt Pavement (RAP), poses a challenge to enduring extremely low temperatures. This study examines the performance of typical Ontario Superpave surface course HMA to thermal cracking. Thermal Stress Restrained Specimen Tests (TSRST) and Disk-Shaped Compact Tension Tests (DC(T)) were conducted on six laboratory prepared hot mixtures with varying RAP contents and Asphalt Binder Performance Grade (PG). The results suggest that the Recycled Hot Mixtures (RHM) do not always withstand the expected critical temperatures, but they could exhibit a lower impact in fracture strength when the extreme low temperature drops by 6°C.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".