Developing Cost Frameworks for Sustainable Water Supply Utility: A Bibliometric Analysis and Systematic Literature Review
Bibliographic record
Abstract
Sustainable water supply utilities involve entities that emphasize long-term viability for the environment, economy, and society in the design, implementation, and management of water supply-related systems and infrastructure.It includes developing and upholding water delivery, distribution, and treatment systems that meet the needs of both the current and upcoming generations while reducing harmful environmental effects.This article employs a bibliometric technique to investigate publication trends between 2018 and 2023, identify the most dominant clusters, and identify potential study areas and future directions, thereby enhancing our understanding of the subject's research trends.The bibliometric study's objective is to describe the cost assessment of water supply utility by identifying activities, issues, and topic interests; providing a detailed explanation of cost assessment; and presenting and analyzing results based on bibliometric data to determine performance, developments, and trends in the field of study.This research conducts a thorough literature review to identify the essential elements required for a comprehensive cost framework.The analysis highlights the necessity of integrating these diverse components into a cohesive framework to ensure effective design, engineering, and utility administration, thereby ensuring both current and future sustainability.
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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 | 0.042 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.225 | 0.189 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".