Feasibility of Stormwater Treatment by Conventional and Lamellar Settling With and Without Polymeric Flocculant Addition
Bibliographic record
Abstract
Abstract Stormwater treatment by lamellar and conventional clarification, with and without flocculant addition, was investigated in Toronto, Ontario, using a pilot-scale rectangular clarifier vessel with removable lamellar plates. During the 2001 to 2003 field seasons, 76 stormwater runoff events were characterized with respect to flow and quality, and further investigated for stormwater treatment. Most stormwater constituent concentrations at this site exceeded those for the U.S. NURP median urban site. A cationic polymeric flocculant dosed at 4 mg/L, with lamellar clarification, provided the best results with a total suspended solids (TSS) removal of 83% at total vessel surface loads up to 36 m/h. The clarification processes produced a concentrated sludge, which was strongly polluted by heavy metals and would require special disposal procedures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".