Sources of Pollutants in Urban Areas (Part 1) - Older Monitoring Projects
Bibliographic record
Abstract
Information concerning source area runoff characteristics during wet weather events can be very important when developing stormwater management plans that incorporate source area controls, or changes in development patterns. This information is also important when calibrating or testing many stormwater models. Unfortunately, this information is not readily available and can be expensive and tedious to collect. However, a substantial amount of these data have been collected over the past several decades, but are not well known. This chapter, and the next, present summaries of these data, specifically source area sheetflow and particulate quality for a variety of areas. Information is presented for many source areas, including urban wet and dry atmospheric deposition, roofs, urban soils, streets and other pavements. Information showing concentrations of conventional pollutants, heavy metals, and selected organic compounds is summarized for major land use categories. The following chapter summarizes additional source area sheetflow information obtained during detailed projects in Alabama and Wisconsin during the 1990s, and summarizes newer data collected elsewhere.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".