Performance Assessment Method for Small- and Medium-Sized Urban Water Systems: Development and Implementation
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
Performance assessment of Small and Medium-Sized Water Systems (SMWSs) is important for operational, tactical, and strategic decision-making. In this study, a performance assessment method has been developed and applied to five drinking water, three wastewater, and two stormwater utilities using 39, 30 and 27 Key Performance Indicators (KPIs) in a semi-arid region. The KPIs were aggregated to determine a performance index using a Technique for Order of Preference by Similarity to Ideal Solution method. K-nearest neighbors and penalty methods were used to estimate missing KPIs data. The results indicated that only two drinking water utilities and one wastewater utility had been rated as ‘high’ performance. None of the utilities in stormwater performance was rated as ‘high’. The developed method can assist decision-makers in evaluating SMWSs performance holistically, build operational management strategies, and identify necessary interventions in overcoming water systems challenges across each urban water system component.
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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 | 0.001 | 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