Assessing urban stormwater toxicity: methodology evolution from point observations to longitudinal profiling
Bibliographic record
Abstract
The quality of aquatic habitat in a stormwater management facility located in Toronto, Ontario, was assessed by examining ecotoxicological responses of benthic invertebrates exposed to sediment and water from this system. Besides residential stormwater, the facility receives highway runoff contaminated with trace metals, polycyclic aromatic hydrocarbons (PAHs), and road salt. The combined flow passes through two extended detention ponds (in series) and a vegetated outlet channel. Toxicity of surficial sediment collected from 14 longitudinally arrayed locations was assessed based on 10 acute and chronic endpoints from laboratory tests with four benthic organisms. Greatest overall toxicity was observed in sediment from sites in the upstream pond, where mortality to amphipods and mayflies reached up to 100%. Downstream pond sediment was less toxic on average than the upstream pond sediment, but not the outlet channel sediment where untreated stormwater discharges provided additional sources of contamination. Macroinvertebrate communities in sediment cores were depauperate and dominated by oligochaetes and chironomids, with minimum densities and diversity at the deeper central pond sites. While sediment toxicity was associated with high concentrations of trace metals and high-molecular weight PAHs, benthic community impoverishment appeared related to high water column salinity.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".