Wet Weather Flow Management in the Great Lakes Areas of Concern
Bibliographic record
Abstract
Under the Government of Canada's Great Lakes Program, the Great Lakes Sustainability Fund and its predecessor programs (the Great Lakes Cleanup Fund and the Great Lakes 2000 Cleanup Fund) were established to implement cleanup actions and strategies that would contribute to the restoration of impaired beneficial uses in environmentally degraded areas (known as Areas of Concern) in the Great Lakes. The Great Lakes Sustainability Fund is administered by Environment Canada on behalf of eight Government of Canada departments. Contributing to impaired beneficial uses are municipal wastewaters generated from the urban centres in the Great Lakes Areas of Concern. These municipal wastewaters include sewage and wet weather related discharges (combined sewer overflows and stormwater runoff). This paper provides an overview of the Municipal Wastewater Program of the Great Lakes Sustainability Fund and highlights the progress made to date under the program towards wet weather flow management and the program's role in developing and demonstrating sustainable approaches and technologies in the Great Lakes Areas of Concern.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".