Local calibration of MEPDG rutting model for Ontario’s Superpave pavements
Bibliographic record
Abstract
The rutting models in the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) have been calibrated to Ontario’s conditions for flexible pavements of Marshall mixes, and have yet to be calibrated for the Superpave materials. This study differs from previous studies in several counts: First, the local calibration database included both Superpave and Marshall mixes. Second, two of the five local calibration parameters (the temperature and traffic exponents) were pre-fixed based on a secondary study of the NCHRP 719 report. Third, both cross-sectional and longitudinal calibrations were performed and compared. It was concluded that the Superpave and Marshall mix pavements should be separately treated in the local calibration and that the cross-sectional and longitudinal calibrations behaved drastically differently in terms of residual errors. A set of local calibration parameters were recommended for future pavement design. It was recommended that trench investigations be done to further validate the results from the study.
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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".