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Record W3014724324 · doi:10.5539/jgg.v12n1p1

Investigation of Groundwater Quality from Selected Wells in Paiko, Northcentral Nigeria

2020· article· en· W3014724324 on OpenAlexvenueno aff
AWEDA Abdulwahid Kolawole, Amadi Akobundu Nwanosike, KYARI Reuben, SAMUEL Abel, SAMSON Bitrus Awu

Bibliographic record

VenueJournal of Geography and Geology · 2020
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterBoreholeAquiferNitrateWater qualityEnvironmental scienceWater wellSewageHydrology (agriculture)AlkalinityEnvironmental chemistryEnvironmental engineeringGeologyChemistryEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Groundwater from hand dug wells and boreholes in Paiko, northcentral Nigeria were subjected to physico-chemical as well as microbiological analysis to determine their suitability for drinking purpose. The water from the hand dug wells are predominantly calcium magnesium chloride (Ca-Mg-Cl) water while those from boreholes are calcium magnesium bicarbonate water (Ca-Mg-HCO3) facies. The results showed elevated cations and anions concentration in the hand dug wells in addition to the water being slightly acidic. Also, the nitrate concentration in the hand dug wells is above the maximum permissible limit of 50mg/l postulated by World Health Organization (WHO) and Nigerian Standard for Drinking Water Quality (NSDQ). Microbiological analysis revealed Total Coliform Count of 100cfu and 360cfu in the hand dug wells and borehole respectively signifying faecal contamination. The study revealed that improper sewage systems as well as poor waste disposal is responsible for the poor water quality as well as elevated concentration of nitrate in hand dug wells, and as such the shallow aquifer groundwater in the area are not safe for drinking purpose with respect to all the parameters taken together.

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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.246
Teacher spread0.229 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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