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Record W4401810466 · doi:10.7770/safer-v12n1-art716

Comparative assessment of ground water quality in Kokrajhar, India.

2023· article· en· W4401810466 on OpenAlexaboutno aff
Omo Yachang, Swdwmsri Brahma

Bibliographic record

VenueSustainability Agri Food and Environmental Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Quality assessmentGeographyRegional sciencePolitical sciencePhilosophyEpistemologyLaw

Abstract

fetched live from OpenAlex

A study was undertaken to understand the comparative assessment of ground water quality of Kokrajhar in both pre and post monsoon seasons. Kokrajhar is witnessing a considerable growth in terms of population and urbanization. Ground water plays a crucial role for consumption and in supporting daily activities of the local population. With the potential risk of groundwater contamination due to various activities, it is essential to assess the quality of this vital resource in order to meet the needs of the local population. In this study, ground water samples were collected from 20 different locations during both pre and post monsoon periods. The ground water samples were tested for 12 different parameters. The geo-locations of the sample points were mapped using GIS software and contour maps were generated for various test parameters. The ground water quality was determined using two methods: The Weighted Arithmetic Index method and the Canadian Council of Ministers of the Environment Water Quality Index method. The result obtained from both the methods have been compared. A very small to some significant changes in different parameters were noted when both pre and post monsoon ground water samples were considered.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.090
GPT teacher head0.424
Teacher spread0.334 · 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.

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
Published2023
Admission routes1
Has abstractyes

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