Sewer Assessment,I/I Assessment and Recalibration Saves Millions
Bibliographic record
Abstract
The Metropolitan Sewer District of Greater Cincinnati (MSDGC, the District) is committed to the elimination of sanitary sewer overflows (SSO) and basement flooding events in their combined and sanitary sewer networks.In meeting this commitment in the Richmond/Orchard study area, the District has completed a Storm Water Removal Program, conducted flow monitoring and hydraulic modeling, and prepared a remedial measures plan to reduce SSO activity and basement flooding complaints.The recommended remedial plan was considered costly.As a result the District undertook to further evaluate area hydraulic and flooding problems with a focus to improve upon the previous studies when it was determined they did not have the benefit of complete and accurate calibration and system geometry data.A hydraulic model, MIKE SWMM, was developed and calibrated using flow monitoring data collected during the study period and verified using historical monitoring data.Model verification included a more complete consideration of flow, volume, stage, and hydraulic conveyance properties throughout the collection system.The study resulted in a combination of system improvements at an estimated cost of approximately one third of the original estimates to reduce SSO and basement flooding occurrences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.011 |
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".