Developing a Model for Basement Flood Relief Works for the New Millennium
Bibliographic record
Abstract
Almost half of the City of Wim1ipeg is serviced by combined sewer systems.The service area is mainly in the older, core area of the City, and comprises approximately 10,500 ha.The combined sewer service area is partitioned into 42 individual sewer districts.Each district has its own lateral, collector and trunk sewer system with at least one river outfall.The combined sewer systems were designed and built from the late 1800s, up to 1960, and reflect the site conditions of the time.Since then increases in impervious area, such as paved parking lots, driveways and wider paved streets, have changed the district hydrology.This led to less stormwater infiltration and higher flows and volmnes of rm1off entering the combined sewer system.Consequently, the conveyance capacity of the sewer system is frequently exceeded, particularly in the older areas.This causes sewer surcharge and backup into basements, with resultant property damage and potential health risks.The City ofWinnipeg initiated a basement flood relief program in the mid-1960s to provide a minimum five-year level of protection to the residents.Since 1977, this program has been developed with computer models based on various versions of the Stormwater Management Model (SWMM).To date, sewer relief works have been implemented in 21 of the City's combined sewer districts.These relief works have been carried out, for the most part, in isolation from other City initiatives.The current climate of fiscal responsibility, heightened public awareness and the introduction of new City infrastructure initiatives mandate a thoughtful and carefully planned program, fully cognizant of current and future planned development in all public sectors. ---~~--•~-~-
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".