Suspended Particulate in Urban Stormwater Ponds: Physical, Chemical and Toxicological Characteristics
Bibliographic record
Abstract
Suspended solids (SS) were sampled in an on-stream stormwater management pond and analyzed for a number of parameters, including particle sizes, density, carbon, inorganic chemistry, metal speciation and toxicity detected by the Microtox Solid Phase bioassay. Primary particles in SS ranged from < 0.24 μm to 44 μm, with D50 = 2.8 μm. Seven inorganic constituents (As, Cd, Cr, Cu, Hg, Pb and Zn) in SS were assessed against the Canadian Sediment Quality Guidelines for the Protection of Aquatic Life and their observed levels were likely to cause adverse biological effects with probable incidence as high as 38%, in the case of Cu. Speciation of metals revealed potential mobility of Cu, Pb and Zn, whose total burdens contained significant oxidizable and reducible fractions. Physico-chemical properties of SS and surficial pond bottom sediment were comparable, and surficial sediment was adopted as a surrogate in further studies. The toxicity assessment of surficial sediment in the pond studied indicated sediment toxicity throughout the pond bottom area outside of the inlet sandy delta. As confirmed by adjunct studies, suspended solids passing through stormwater ponds were polluted and could cause toxic effects in downstream waters. However, the risk of toxic effects would depend on concentrations and fluxes of polluted suspended solids in pond outflow, and transport and settling processes in the receiving waters. For the baseflow conditions addressed in this study, such a risk is relatively low and would be limited to depositional areas, where these solids could accumulate. In other areas, escaping solids remain in transport and/or are diluted with cleaner sediment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".