Modeling Long-Term Flexible Pavement Performance of Ontario Highways
Bibliographic record
Abstract
The Ministry of Transportation of Ontario (MTO) uses several multiple performance indices in the newly implemented MTO Second Generation Pavement Management System (PMS/2). These indices can be used jointly or individually to assess pavement performance in terms of overall Pavement Condition Index (PCI), ride comfort index (RCI), International Roughness Index (IRI), and Distress Manifestation Index (DMI). Each of the evaluation indices may be used to address current pavement serviceability and predict future trends in functional adequacy, such as pavement structural strength and distresses. This study presents the long-term flexible pavement performance observed in the field after reconstruction or rehabilitation, as represented by a number of pavement maintenance and rehabilitation (M&R) strategies that are commonly used for preservation of the Ontario highway network. The paper concludes with discussions and recommendations to modify the existing pavement performance prediction models that are currently used in the PMS/2 through correlation with the actually observed pavement performance trends for each type of pavement rehabilitation/reconstruction treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".