Geospatial assessment of groundwater quality using Water Quality Index and Inverse Distance Weighted techniques
Bibliographic record
Abstract
Groundwater is the main source of domestic and industrial activities in the city of Lahore and Kasur due to meagre resources of surface water. The current study was conducted to investigate the groundwater quality for drinking purpose and to identify the hydrochemistry of groundwater using Canadian Council of Ministers for the Environment Water Quality Index and Gibb’s graph. 40 water samples were taken from different areas of Lahore city and 19 samples were collected from Kasur city. These samples were tested by 15 physiochemical parameters (pH, EC, TDS, TH, Turbidity, HCO3, Cl, Ca, K, Mg and Na) and heavy metal (Zn, Cu, Fe and As). According to water quality index model results, groundwater of Lahore city lie between excellent to the marginal category, whereas the groundwater of Kasur fall under good to poor category. Evaporation and rock water interaction influence were dominant in both of the study areas, which clearly indicates the interaction between rock and percolated water geochemistry. It is recommended that the government should install more tube wells at a considerable depth to ensure contamination free and excellent drinking water at the consumer’s end
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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 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".