Reducing CSOs and giving the river back to the public: innovative combined sewer overflow control and riverbanks restoration of the St Charles River in Quebec City
Bibliographic record
Abstract
After the construction of its wastewater treatment plants, the City of Quebec began to implement overflow control in wet weather to ultimately meet the effluent discharge objectives, i.e. no more than two overflows per summer season in the St. Lawrence River and no more than four in the St-Charles River. After several years of studies to determine which management strategies would best suit the purpose, and to propose optimum solutions, a first project to implement optimal and predictive management in real time, called "Pilot", came to life in 1999. Construction in phases soon followed and the work was completed in the fall of 2009. As a result, requirements with regard to environmental rejects were met in two sectors, namely the St-Charles River and the Jacques-Cartier Beach, and aquatic recreational activities could resume. Meanwhile, the City also worked at giving back access to the water courses to the public by developing sites at the Jacques-Cartier Beach and in the Bay of Beauport, and by rehabilitating the banks of the St-Charles River.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".