Pavement Rehabilitation Design for City of Ottawa OR-174 Composite Pavement Section
Bibliographic record
Abstract
The OR-174 is major arterial highway in the City of Ottawa connecting the Blackburn Hamlet and Orleans communities to the rest of Ottawa. A 3.9 km four lane section (2 lanes each way) of the highway is a composite pavement consisting of a 1959 concrete pavement overlayed with asphalt pavement. This section of high way is experiencing a variety of maintenance issues including development of humps at joint and crack areas. Stantec Consulting Ltd. (Stantec) was contracted by the Cit y to perform a detailed pavement evaluation on this section of the OR-174 to develop a pavement rehabilitation design strategy. As part of the evaluation process a variety of evaluation techniques were utilized to collect data on the roadway structure including Falling Weight Deflectometer (FWD) testing, Ground Penetrating Radar (GPR) surveys, Visual Condition Assessments and Subsurface Investigations. This report provides background and a summary of th e data collected and how it was analyzed to assist in the evaluation of six different rehabilitation / reconstruction alternatives for the OR-174 project area. Results of the evaluation of the various alternatives are provided in the paper including development of preliminary designs, maintenance and rehabilitation schedules, initial potential cost estimates and life cycle analysis on the three most promising options. For the covering abstract of this conference see ITRD record number 201211RT334E.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".