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Record W2127138574 · doi:10.5897/ijps.9000296

Hydrogeophysical investigation of groundwater potential in Emu kingdom, Ndokwa land of Delta State, Nigeria

2009· article· en· W2127138574 on OpenAlexaboutno aff
Julius Otutu Oseji, O Ujuanbi

Bibliographic record

VenueInternational Journal of the Physical Sciences · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsAquiferGroundwaterBoreholeVertical electrical soundingGeologyQuarter (Canadian coin)Hydrology (agriculture)Geotechnical engineeringGeography

Abstract

fetched live from OpenAlex

A study of 10 vertical electrical soundings from different quarters of Emu kingdom using Schlumberger array were undertaken. This is an attempt to obtain useful information on the aquifer distribution within the area and hence delineate possible site boreholes could be drilled for potable and sustainable water supply. Based on the geoelectric section which is in agreement with the driller’s log, the best environments for sustainable water supply were identified. This coincides with the third layer of the aquifer in Emu kingdom and consists of medium-grained sand formation. The average depth to this aquifer is 45 m whose thickness is not defined at Obiogo since it is the last layer, but in other parts of Emu-Kingdom, the thickness ranges from 45.00 m in Ikosa quarter to 95.00 m in Etevie quarter. The resistivities of these layers vary from 1000.00 - 3000.00 ohm-m. The aquifer system of Emu Kingdom has an overlying confining bed without an underlying confining layer, hence it is leaky or semi-confined. The thickness of this confining upper bed is greater at Ebendo and Obodoeti, hence in the event of pollution, groundwater at Obiogo, Ikosa and Etevie quarters in Emu-Uno are highly contaminated.   Key words: Vertical electrical sounding, groundwater potential, aquifer, Ebendo, Obodoeti Obiogo, Etevie and Ikosa quarters in Emu-Uno.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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

Citations15
Published2009
Admission routes1
Has abstractyes

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