Groundwater quality and heavy metal assessment of Ranbir Singh Pura, Jammu and Kashmir
Bibliographic record
Abstract
Groundwater is the only source available for drinking in the study area. Water samples from 25 sampling sites were collected (handpumps, motors and borewells) for period (October to November) 2022 with the aim to evaluate the water suitability for irrigation and drinking purpose. Physico-chemical parameters (n = 15), heavy metals and water quality index (WQI) were determined to check the drinking water suitability. The obtained results were then compared with the BIS-2012 and WHO drinking water standards. Results indicate 52% of water samples from study area under good category of WQI. Groundwater was found suitable for irrigation purposes according to different irrigation indices except permeability index for which 60% samples were found unsuitable. According to heavy metal evaluation index, groundwater of the study area found to be highly contaminated with arsenic (As), copper (Cu), lead (Pb) and chromium (Cr). High contamination of Fe (heavy metal pollution index [HPI] = 120.45) and Cr (HPI = 7240.8) was recorded as per HPI. For different age groups in the study area, hazard quotient value for Cr and As was found at risk. Study region was found contaminated with the Cr, As and Pb concentrations which impact the health of locals. So, continuous monitoring of the groundwater of study area is suggested.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".