CPR Techniques in Canada - 18 Years of Performance Experience
Bibliographic record
Abstract
In the summer of 1989, the Ministry of Transportation of Ontario (MTO) undertook the rehabilitation of an exposed concrete pavement exhibiting various distress manifestations. Highway 126 in Southwestern Ontario is a four-lane divided arterial with 22,000 AADT and 9.6% commercial traffic in year 2000. The existing pavement constructed in 1963 consisted of 230 mm mesh reinforced Portland Cement Concrete (PCC) pavement with dowelled joints at a spacing of 21.3 m. The rehabilitation of the highway in the northbound lanes consisted of using the latest concrete pavement restoration (CPR) techniques, material specifications and construction methods. The rehabilitation techniques included full depth repair, partial depth repair, diamond grinding and joint sealant replacement on the northbound lanes which had experienced moderate deterioration. The southbound lanes received a 180 mm thick plain jointed unbonded PCC overlay to address the severe 'D' cracking and spalling at all the joints and cracks. This paper will discuss the eighteen-year evaluation of this rehabilitated pavement in terms of smoothness measurement using California Profilograph, roughness measurements using the Automatic Roughness Analyzer (ARAN), frictional resistance measured with the ASTM brake-force trailer, and Pavement Condition Ratings. Overall, the eighteen-year performance of the rehabilitated concrete pavements has been good with acceptable levels of ride quality, frictional resistance and distress propagation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".