A Case in Support of Continuous Modeling for Stormwater Management System Design
Bibliographic record
Abstract
Stonnwater management systems for new urban development have been traditionally designed and analyzed with the aid of computer models employing design stonn events [such as the Soil Conservation Service (SCS) temporal distribution], rather than continuous modeling using long tenn historical rainfall data and associated frequency analyses. It has generally been accepted that the latter method provides a more rigorous and realistic design; however, the differences in the results (i.e. designs) generated by the two methods have not typically been understood during the planning and design process. Tlus chapter describes a case study in the Town of Milton (Sixteen Mile Creek Watershed) in which, based on a unique oppotiunity, both methods were applied in the analysis and preliminary design of end-of-pipe stonnwater management facilities. The different flow and storage regimes generated by the alternate methods are highlighted, along with a number of modeling and physical factors which are considered to contribute to the differing results.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".