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Record W2253872370

Water quality evaluation of shallow wells in Kokrajhar Town of Assam, India

2014· article· en· W2253872370 on OpenAlexaboutno aff
Babulal Das

Bibliographic record

VenueInternational Journal on Environmental Sciences · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsTube wellWater qualityPopulationGroundwaterQuarter (Canadian coin)ChlorideTotal dissolved solidsPhosphateHeavy metalsToxicologyGeographyEnvironmental engineeringEnvironmental scienceWater resource managementEnvironmental chemistryChemistryGeologyEcologyBiologyArchaeologyEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Kokrajhar town is the head quarter of Bodoland Territorial Area District (BTAD). This is one of the developing towns of western Assam. The town covers an area 8.24 sq km. There are ten wards in the town. The population of the town is 31972. The people of the town mainly depend on groundwater for drinking and their daily other needs. The major types of sources are ring well, tube well and few deep tube well. In this work, an attempt has been made to evaluate the water quality of 10 of the most-used shallow tube wells by monitoring the common quality parameters like temperature, pH, conductivity, total dissolved solids, hardness, bicarbonate, chloride, sulphate, phosphate, fluoride, common metals like Ca, Mg, Na, K, Fe and trace metals like As, Cd, Cu, Mn and Zn. The water is characterized by very high phosphate (0.08 to 0.22 mg/L) and iron content (0.2 to 1.1 mg/L) exceeding the maximum prescribed limit of World Health Organization in many cases. Many of the sources have Cd (0.039 to 0.142 mg/L) above WHO permissible limits. The study has shown important results indicating that even in an under-developed area, water quality problems exist. The results have been explained on the basis of known water-related problems associated with the people living in the area.

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)0.006
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 score0.131
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.050
GPT teacher head0.346
Teacher spread0.296 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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