Drinking Water Quality Assessment in Tetova Region
Bibliographic record
Abstract
Abstract: Problem statement: The quality of drinking water is a crucial factor for human health. The objective of this study was the assessment of physical, chemical and bacteriological quality of the drinking water in the city of Tetova and several surrounding villages in the Republic of Macedonia for the period May 2007-2008. The sampling and analysis are conducted in accordance with State Regulation No. 57/2004, which is in compliance with EU and WHO standards. A total of 415 samples were taken for chemical, physical and bacteriological analysis. Approach: We had used the Canadian Drinking Water Quality Index (DWQI) for the quality assessment of drinking water. Results: The results of the samples taken in Tetova point to better hygienic and sanitary conditions than in the rural drinking network, mainly due to improper disinfection practices. The results show that the highest water quality was recorded at the SEEU (DWQI = 92.69), whereas the lowest quality at Shipkovica (DWQI = 63.18). Conclusion: This study strongly recommends the immediate correction of these issues to protect the health of population from water borne diseases as well as regular monitoring of the drinking water quality in the region. Key words: Drinking water quality, drinking water quality index, bacteriological parameters,
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".