A comparative study of water quality using two quality indices and a risk index in a drinking water distribution network
Bibliographic record
Abstract
This study compares the Canadian Council Water Quality Index (CCME WQI) and the Arithmetic Water Quality Index (WAWQI) methodologies for determining the quality of water in the city of Azogues (Ecuador). Additionally, a drinking water quality risk index (IRCA) was determined to evaluate the degree of risk of disease occurrence related to water consumption. The data generated came from the analyses of twelve physicochemical parameters (pH, turbidity, colour, total dissolved solids, electrical conductivity, total hardness, alkalinity, nitrates, phosphates, sulfates, chlorides, residual chlorine) from 172 samples of water over six months. The calculated average value of CCME WQI (97.59 ± 1.08) indicates that 100% of the drinking system was of ‘excellent’ quality. The WAWQI average value was calculated to be 26.36 ± 1.13 indicating that 16.67% of the distribution system was of ‘excellent’ quality and 83.33% of the distribution water was of ‘good’ quality. The IRCA calculated in all the distribution zones is between 0 and 5% and therefore, the distributed water is considered suitable for human consumption and is rated at the no-risk level. Furthermore, WAWQI is influenced by parameters with low maximum allowed concentration (for example, turbidity value 1 NTU in the Ecuadorian standard was used instead of 5 NTU recommended by the WHO); conversely, CCME-WQI is influenced by parameters with a high maximum allowed concentration (no parameter exceeded the norm in this study). The IRCA is a support instrument to guarantee that the water supplied by the provider companies complies with the characteristics established for drinking water.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.016 | 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 teacher head, 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".