Mid-life comparative field study investigating stormwater management between a permeable pavement and asphalt parking lot
Bibliographic record
Abstract
As a result of increasing density in the built environment around our cities, there is an ever growing amount of effective impervious area (EIA) which in turn results in greater amounts of runoff due to rain events. While minimizing hard surfaces is a method to minimize EIA, it is not always practical. A common method to better manage stormwater has been the installation of permeable pavement in parking lots. This study investigated the efficacy of permeable pavements in a comparative study against asphalt, at a point 10 years after construction, with the goal of demonstrating the continued benefits to water quality and minimized runoff from the permeable pavement site. The field study, conducted in Burnaby, BC between two parking lots, yielded promising results which demonstrated that with routine maintenance, a permeable pavement system is able to continue minimizing downstream runoff for most types of rain storm events and is able to continue minimizing contaminant effluent concentrations of certain contaminants when compared to an asphalt site.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".