Flow Needs for City of Detroit Customers through 2050
Bibliographic record
Abstract
The city of Detroit Water and Sewerage Department (DWSD) provides wastewater services for the city and 77 surrounding communities.A wastewater master plan (WWMP) has been developed for the department to provide guidance on sewer extensions and improvements that will be required to the regional collection and treatment system over the next 50 years.As part of the development of this plan, an analysis of wastewater flow needs has been completed for the city of Detroit and the surrounding communities.These flow needs have been defined in terms of wastewater flow rates that are projected to be generated within the system under both dry weather and wet weather conditions.Wastewater flows for which projections are required are considered to consist of three components: (i) sanitary sewage flow, (ii) dry weather inflow/infiltration (DWII) or non-sewage flow, and (iii) wet weather flow (WWF).These three components are projected to future years separately, based on the factors that impact these flows.Results have been used for evaluating potential capacity constraints of the regional system for the next 50 years.An additional goal of the analysis was to develop a uniform technical standard for assigning contract capacities for existing and new customers.This standard has helped to define what flows the regional system would be expected to accommodate versus what flows would be the responsibility of the customers to handle.Results of this analysis have been provided to the department for their use in future contract negotiations.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".