Impact on the Fate of Toxic Contaminants in the Toronto Waterfront — Should the Toronto Main Sewage Treatment Plant Outfall Be Moved Farther Offshore?
Bibliographic record
Abstract
Abstract A fate model, TOXFATE, is coupled with a hydrodynamic model of the waters off the Toronto waterfront, Lake Ontario. The Toronto waterfront is here defined as a rectangular area, 48 km long by 10 km wide, of the lake delimited on the west by Etobicoke Creek and in the east by the Rouge River. Data were collected in 1987 in support of the Toronto Main Sewage Treatment Plant (STP) pilot site study, Municipal and Industrial Study for Abatement (MISA). It provides an excellent baseline database. The object of the fate-modeling study is to assess the change in organics concentration if loadings from the Main STP and other local sources were changed or the outfall location moved farther offshore. Loadings of contaminants from local sources in the Toronto waterfront area are between 0.5% to 25% of contaminants that enter Lake Ontario from other sources. Results show that if sources of local loadings were reduced, changes in water concentrations would be noticeable within 1 to 2 kilometres from shore. Only a small area of the waterfront is affected directly by local sources since waters in the Toronto waterfront area are replaced approximately every 9 days (as computed from the hydrodynamic simulation). Therefore, toxic contaminants that enter from local sources are readily dispersed in the rest of the lake. Simulations also show that the extension of the Toronto Main STP outfall to a new location farther offshore will result in a dilution of toxic contaminants 10 times greater than that obtained at the present STP outfall. A complete set of figures, including an interactive analysis of the computer simulations, is available on the Web site www.butx.com/toronto.
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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 | 0.013 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".