Non-Revenue Water (NRW) is a challenge for Global Water Supply System Management: A case study of Dhaka Water Supply System Management
Bibliographic record
Abstract
Non-revenue Water (NRW) is an important component of commercial water system management. NRW is the result of pipelines leakage, improper, illegal service connections and theft water. NRW contributes system loss that is a buzzword. Actually, NRW is uncounted water that has been produced but it is confirmed to be lost before it consumes the customer. This matter agitates for all concern and specially it affects the whole economy. Dhaka Water Supply and Sewerage Authority (DWASA) is one of the main utilities in Dhaka City and it is the mostimportant sector of the Government of Bangladesh. The potable water distribution network has been installed at the whole area of the city and it covers periphery of the city and its extension is going from N. Gonj to Tongi as well as surrounding area of this city. Non-revenue water surveys were conducted on specific fields and areas that were selected randomly. It would be gradually becoming a serious issue affecting the interest of all concerned andwould be one of the major crises to be solved with techno-managerial concept.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".