Water Quality in Drinking Water Distribution Systems: A Whole-Systems Approach to Decision Making
Bibliographic record
Abstract
Water utilities are responsible for continuously providing safe water to consumers through their drinking water distribution systems. Avoiding siloed approaches that may lengthen critical response times in the case of a water quality hazard can be accomplished through a whole-system approach. To achieve this objective, providers need to pursue the state-of-the-art knowledge and techniques across all facets of water quality management as our understanding of these complex infrastructures continually evolves.This study provides a comprehensive and up-to-date bibliometric study of water quality in drinking water distribution systems over the first twenty years of the 21st century. Analysis of the relevant literature reveals how the research landscape has expanded in terms of number of publications made, variety of topics, and geographic diversity. Each region has a unique ‘research identity’ in the different topics focused upon, yet the presented inter-dependency of factors impacting water quality emphasises the opportunities for sharing of best practices.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".