Stormwater Quality Modeling Improvements Needed for SWMM
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The U.S. Enviromnental Protection Agency's (USEPA) Stonnwater Management Model, or S WMM, is a large, relatively complex software package capable of simulating the transformation of precipitation to urban nmoff and the transport of the runoff from the grmmd surface through pipe/channel networks and storage/treatment facilities and finally to receiving waters. The model can be used to simulate a single event or a long continuous period. The original model was developed by Metcalf and Eddy, Inc. in association with the University of Florida and Water Resources Engineers, Inc. in 1971. Over the last three decades there have been many significant improvements and enhancements to the model's capabilities. However, the model's algorithms used to simulate the accumulation and transport of storm water pollutants have rarely been addressed or significantly improved. With the recent development of the USEP A's NPDES storm water program and the ongoing development of the TMDL program and the continuing interest and concern associated with storm water pollution throughout the developed world, the need to significantly improve the stormwater quality modeling capabilities ofSWMM is greater now than ever before.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it