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Record W4414056475 · doi:10.1680/jenes.24.00073

Groundwater quality and heavy metal assessment of Ranbir Singh Pura, Jammu and Kashmir

2025· article· en· W4414056475 on OpenAlexvenueno aff
Somalya Dogra, Komal Sharma, Navdeep Singh, Vikas Sharma

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater and Watershed Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterIrrigationHazard quotientWater qualityContaminationArsenicPollutionWater pollution

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.242
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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