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Record W4402851496 · doi:10.5539/ep.v13n2p11

Dynamics of Uranium Concentration in Groundwater of Mineralized Formations, Western Edge of Aïr Massif, Agadez Region (North Niger)

2024· article· en· W4402851496 on OpenAlexvenueno aff
Illias Alhassane, Abdou Babaye Maman Sani, Issa Malan S. Souleymane

Bibliographic record

VenueEnvironment and Pollution · 2024
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsMassifGroundwaterUraniumGeologyGeochemistryEnhanced Data Rates for GSM EvolutionMineralogyGeomorphologyGeotechnical engineeringMetallurgyEngineeringMaterials science

Abstract

fetched live from OpenAlex

The study area is located in Arlit region, which is a semi-arid zone and where groundwater is the main source of water resources. In this area, the host formations of uranium mineralization are also aquifers. Thus, the waters of these aquifers naturally contain significant amounts of uranium. The consumption of water from these wells can constitute a proven health risk for population. It is therefore urgent to analyses the groundwater from these aquifers in order to determine the uranium content of these waters. The objective of this study is to determine the uranium content in these aquifers. A methodological approach based on hydrochemical analysis methods has shown that the groundwater sampled contains very high levels of uranium ranging from 0.26 mg/L to 0.0024 mg/L, which is unsuitable for any human activity, outside the processing of uranium ores. In addition, these waters naturally contain uranium related to the geological context of this area. However, other external sources such as mining activities bring uranium through water seepage or accidents. Note that these waters are not used by population because they are located in the mining area. The water from these wells is used in the processing of uranium ore for the purpose of extracting uranium contained therein. This study made it possible to identify the uranium content of groundwater in mineralized formations of study 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)0.000
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 score0.242
Threshold uncertainty score0.225

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 science0.0000.000
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 head0.010
GPT teacher head0.196
Teacher spread0.185 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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