Asphalt binder selection for future Canadian climatic conditions using various pavement temperature prediction models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past 20 years, climate scientists have predicted that anthropogenic climate change would lead to an increase in global temperatures. In addition, the trends were predicted to further aggravate in the near future. Recent studies stated that this climate change has had a significant impact on pavement performance. As asphalt binder is susceptible to changes in temperature, it is necessary to understand the influence of climate change on asphalt binder grade selections. Therefore, the aim of this study is to estimate the new asphalt binder grades for Canada using the projected climate data. To achieve this, average seven-day maximum pavement temperature and a minimum pavement temperature were determined using the three different pavement temperature prediction models: SHRP, LTPP and EICM to estimate the asphalt binder (PG XX – YY). This paper presents a summary of revised asphalt binder grades for 28 different locations across Canada.
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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 | 0.001 | 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 | 0.001 | 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) | 0.001 | 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 it