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Record W2163828859 · doi:10.1155/2009/971242

Water Quality Assessment of Groundwater Resources in Nagpur Region (India) Based on WQI

2009· article· en· W2163828859 on OpenAlexaff
Prashant N. Rajankar, S.R. Gulhane ., D. H. Tambekar, D. S. Ramteke, S. R. Wate

Bibliographic record

VenueJournal of Chemistry · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsImpact
FundersNational Environmental Engineering Research Institute
KeywordsGroundwaterWater qualityMonsoonHydrology (agriculture)Tube wellSummer seasonEnvironmental scienceGeographyGeologyMeteorologyEcology

Abstract

fetched live from OpenAlex

Water quality index (WQI) has been calculated for different groundwater sources i.e. dug wells, bore wells and tube wells at Khaperkheda region, Maharashtra (India). Twenty two different sites were selected in post monsoon, winter and summer season. And water quality index was calculated using water quality index calculator given by National Sanitation Foundation (NSF) information system. The calculated WQI showed fair water quality rating in post monsoon season which then changed to medium in summer and winter seasons for dug wells, but the bore wells and hand pumps showed medium water quality rating in all seasons where the quality was slightly differs in summer and winter season than post monsoon season, so the reasons to import water quality change and measures to be taken up in terms of groundwater quality management are required.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.305
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations76
Published2009
Admission routes1
Has abstractyes

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