Ten Year Performance Evaluation of Unbonded Concrete Overlay and Jointed Plain Concrete Pavement: A Toronto Case Study
Bibliographic record
Abstract
Heavy, slow moving traffic can be extremely damaging to asphalt pavements. The City of Toronto was observing the rapid deterioration of the pavements at an urban intersection with high volumes of transit bus traffic. The heavy traffic was causing severe rutting and other safety concerns. In collaboration with the Cement Association of Canada, the City of Toronto elected to rehabilitate the high traffic intersection of Bloor Street and Aukland Road using Portland cement concrete. As part of this project, the city constructed its first unbonded concrete overlay and reconstructed an adjacent area as a conventional Jointed Plain Concrete Pavement. The rehabilitation activities were completed during the summer of 2003. Instrumentation was installed by University of Waterloo researchers to monitor and evaluate the long-term performance of the rehabilitated pavements. This paper presents an overview of the existing conditions, design, construction and instrumentation of the Bloor and Aukland site and a ten year performance evaluation of the rehabilitated pavements. The results of this study show that concrete overlays and inlays are excellent rehabilitation options for urban pavements subjected to high volumes of heavy traffic. Both the unbonded overlay and Jointed Plain Concrete Pavement sections have demonstrated excellent performance to date. The pavements are in very good condition visually, ride quality remains excellent and the recurrence of the regular rutting and shoving problems that were being observed prior to rehabilitation has been mitigated. Significant remaining life is expected from the concrete pavement sections at Bloor and Aukland. For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".