Application of CCME WQI to evaluate feasibility of potable water availability: A case study of Tehri dam reservoir
Bibliographic record
Abstract
In the present research work, the Canadian Council of Ministers of the Environment water quality index 1.0 (CCME WQI 1.0) was applied to assess water quality of Tehri dam reservoir by using the drinking water standard prescribed by the WHO (1999) and BIS (IS:10500, 1991). The physico-chemical parameters, ions concentration and heavy metals concentration used in the index calculation were total dissolved solids, pH, alkalinity, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total hardness, calcium, chloride, phosphate, sulphate, nitrate, total coliform (MPN/100 ml), turbidity, zinc, manganese, lead, nickel, iron and chromium. It was observed during the course of study that at all the four sites BOD, phosphate and total coliform showed greater deviation from the objective values. Total coliform was found to be more deviated from the normal values. Few important parameters were observed beyond the permissible limit for many times. The values of water quality index have shown that most of the sites are not fit for drinking purpose. Finally it was concluded that reservoir water should not be consumed for drinking purposes frequently without proper treatment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".