Urban drainage and highway runoff in cold climates: conference overview
Bibliographic record
Abstract
This overview of research findings presented at the conference on urban drainage and highway runoff in cold climates starts with generation of urban runoff and snowmelt, followed by snowmelt and winter runoff quality, best management practices for urban snowmelt and winter runoff, and snow management in urban areas. Research on the urban hydrological cycle is lagging behind the needs in this field, particularly in terms of data availability. The current studies of winter urban runoff quality focus on road salts in the urban environment and their environmental effects. The needs for better source controls in salt applications, improved management of chloride-laden runoff, and selective adoption of environmentally safer alternative de-icers were reported. Adaptation of the conventional stormwater best management practices (BMPs) for winter operation remains a challenge. The first step in refining the existing BMPs for winter operation is to advance the understanding of their operation, as reported for some cases at the conference. Finally, snow management in urban areas may require local storage of fresh (unpolluted) snow and disposal of more polluted snow at central snow disposal sites.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".