Climate Change Implications for Asphalt Binder Selection in Pavement Construction across Ontario
Bibliographic record
Abstract
The climate in Canada has warmed and will continue to warm faster in the future, which will result in more intense and frequent temperature variations. Asphalt binder selection based on the Superpave performance grade (PG) system relies on historic climatic conditions in relation to the expected in-service temperature range of the flexible pavement. In view of climate change, it is crucial to investigate the extent to which pavement surface temperatures will be affected by ambient conditions of the future in order to assess the relative impact on the appropriate PG for more durable and resilient pavement construction. In this study, the latest long-term pavement performance (LTPP) model was used to determine the asphalt pavement surface temperatures. For different representative concentration pathways (RCP), the relative impact of climate change on pavement temperature extremes and thereby appropriate PG to meet projected pavement temperatures was assessed using the LTPP models. The results of this study indicate that in the future, climate variations will cause changes to asphalt binder grades across the examined locations in Ontario, which depend on the severity of the projected warming. This research offers useful suggestions that can be incorporated by the road agencies and designers towards adaptation of pavement construction materials suitable to the changing climate.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".