Twelve Towns Retention Treatment Facility System Modeling
Bibliographic record
Abstract
The Retention Treatment Facility (RTF) for the Twelve Towns Drainage District of the Southeastern Oakland County Sewage Disposal System (SOCSDS) in Michigan is authorized to discharge treated combined sewer overflow (CSO) to the Red Run Drain through a National Pollutant Discharge Elimination System (NPDES) permit.In an effort to comply with the requirements of the Federal Clean Water Act (PL 92~500 of 1972), Oakland County needed to evaluate the perfom1ance of the RTF and determine any necessary improvements to achieve that compliance.An XP-SWMM computer model was developed to assess the performance of the RTF and evaluate alternatives to comply with the requirements of the NPDES permit that governs the RTF.The computer model provided a mecha~ nism to perform the .assessment of the most cost-effective and feasible means for implementing system improvement to reduce the number and volume of CSO.The improvements to the system were accomplished by additional storage of CSO, removal of storm water inputs to the RTF, and improvements to maximize the use of the existing interceptor system.The analysis of the RTF and proposed improvements was conducted with respect to the state regulatory agency, the Michigan Department of Environmental Quality (MDEQ) presumption approach for "adequate treatment."MDEQ -• • -----• --• -----• c-=--:---:--
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".