Trace metal levels in sediments deposited in urban stormwater management facilities
Bibliographic record
Abstract
Characteristics of solids recovered from stormwater best management practice (BMP) facilities, including stormwater ponds, constructed wetlands, an infiltration basin, a biofilter, a stormwater treatment clarifier, and three-chamber oil and grit separators were described with respect to their metal chemistry. The reported trace metal concentrations in BMP sediments were assessed against the Ontario Sediment Quality Guidelines. Between 80 to 100% of all samples were marginally-to-intermediately polluted by Cd, Cr, Cu, Fe, Pb, Mn, Ni and Zn. Severe pollution of sediments was noted for Cr (122 microg/g), Cu (151 and 196 microg/g), Mn (1,259 and 1,433 microg/g), and Zn (1,116 microg/g), at several facilities studied, and even higher levels of metals were reported in the literature for certain oil and grit separators. With respect to individual BMPs, the severe pollution was found in sediments from oil and grit separators (for Cd, Cr, Cu, Pb and Zn), the stormwater clarifier sludge (Cu, Mn and Zn), a biofilter (Cu and Mn), an industrial area stormwater pond (Cu only), and a commercial/residential pond (Cr only). Finally, the chemical pollution of pond sediment triggered toxicity testing at some of the facilities studied, and sediment toxicity was confirmed at several 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".