Performance of Permeable Pavements in Cold Climate Environments
Bibliographic record
Abstract
The University of Guelph and Toronto Region Conservation Authority have recently initiated a research collaboration to evaluate the performance of permeable pavement in cold climate environments. Permeable pavement offers a means to reduce runoff, improve water quality and minimize thermal impacts to receiving water systems. However, there is continuing concern and uncertainty regarding the long term performance of these systems. In particular the harsh winters, which occur throughout Ontario and the associated sanding and salting of roadways, have a detrimental effect on both infiltration performance and the quality of the infiltrated water. Sanding of parking facilities can clog the voids within the pavement and, in extreme circumstances, essentially render the pavement impermeable. Even if pavement facilities are not sanded or salted during winter months contaminants and fine particulate matter are still introduced through the day-to-day flow of vehicle traffic. The hydraulic performance of porous pavement can be improved and even restored if regular maintenance is performed and fines removed. Numerous permeable parking facilities, of varying ages, exist throughout Ontario but there are few comprehensive studies evaluating pavement performance within Ontario. In this paper performance issues associated with Ontario conditions will be explained and details of the collaborative permeable pavement research project will be presented.
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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) | 0.007 | 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; both teacher heads agree on what is shown here.
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".