Climate Change Challenges for Flexible Pavement in Canada: An Overview
Bibliographic record
Abstract
This paper provides an outlook on the effects of climate change and the severity and frequency of extreme weather events on the performance of flexible pavements across North America. Now more than ever, the climate is changing at a rapid pace, which will alter long-term environmental loading parameters and extreme weather events. Such alterations will pose implications for the design, maintenance, and rehabilitation of flexible pavements, especially in terms of their serviceability, safety, and functionality. In northern Canada, roads are founded on various terrain types, including thaw-sensitive ice-rich permafrost underlying terrains. Such roads have experienced signs of embankment and pavement damage, which are usually induced by the degradation of the underlying permafrost due to climate change. Therefore, the development and implementation of new permafrost thaw mitigation techniques for vulnerable roads are essential and will be discussed in this paper. Resilient flexible roads should be designed to withstand the conditions that are likely to occur during their design life, taking into account the impact of the climate change on pavement performance in response to daily and seasonal changes in heat, precipitation, freeze–thaw cycles, and extreme weather events.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".