A comparative study of ground water quality and water quality index of certain selected areas situated around Tumkur city, Karnataka
Bibliographic record
Abstract
Ground water is believed to be comparatively clean and free from pollution than surface water. Prolonged discharge of domestic sewage and solid waste causes the ground water to become polluted and create health hazards, but the National Water Policy (2002) states, adequate clean water should be provided to the entire population both in urban and rural areas. Therefore the ground water samples from 15 locations of 5 selected areas namely, Kadaba, Kallambella, Honnudike, Hebbur and Kunigal of situated around Tumkur city have been collected from August to December, 2007 and analyzed for physico-chemical parameters. The values obtained were compared with standards prescribed by ISI and WHO. The data have revealed that certain water samples from Kallambella, Kadaba and Honnudike area have high nitrate level and are of immediate health concern. The water samples of Kallambella area were found to be too hard. The Canadian Council of Ministers of The Environment (CCEM) water quality index (WQI) values were calculated fro a few samples of selected areas and compared with the approved values. The results so obtained would account for the fact that the water samples from Hebbur (S 1 ) and Kunigal (S 2 ) area are of excellent quality; samples (S2) of Kadada area are of good quality, samples (S1) of Honnudike area are of fair quality whereas samples (S 2 ) of Kallambella area are of marginal quality.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".