Applications of Artificial Neural Networks in Urban Water System
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
This paper summarizes an extensive review on the applicability of Artificial Neural Networks (ANNs) in urban hydraulics and hydrology. The identified areas for ANN application include rainfall — runoff — sewer flows, snowmelt — runoff-sewer flows, stormwater and Combined Sewer Overflow quality modeling, Total Loading Analysis, and Real Time Control. This paper also introduces the results of two recent ANN applications in City of Edmonton, Alberta, Canada. One is the early warning system for the Enhanced Preliminary Treatment (EPT) facility to treat the wet weather flow at the Goldbar wastewater treatment plant and the other is the prediction of Combined Sewer Overflow (CSO) based on monitored rainfall data.
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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 | 0.000 | 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) | 0.001 | 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