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Record W1937358696 · doi:10.53704/fujnas.v2i2.27

Studies of Water and Sediment Quality of Owalla Dam, Osun State, Nigeria

2013· article· en· W1937358696 on OpenAlexaboutno aff
N. Abdus-Salam

Bibliographic record

VenueFountain Journal of Natural and Applied Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentWater qualityEnvironmental scienceEnvironmental chemistryPollutantTotal dissolved solidsHydrology (agriculture)GeologyEnvironmental engineeringChemistryGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

Dam water and sediment were collected from ten different locations on Owalla dam to evaluate the quality of the water. The average values of most physical-chemical parameters, the pH, temperature, total dissolved solid (TDS), NO3-, total hardness (TH) were within World Health Organization (WHO) and United State Environmental Protection Agency (USEPA) guidelines for drinking water. There was correlation between the results of Biochemical Oxygen Demand (BOD), sulphate and phosphate which were higher than the USEPA, Standard Organization of Nigeria (SON) or Canadian standard for drinking water. This is an indication of high load of organic pollutants. The dam sediments are texturally immatured coarse sands dominantly comprised of sub-angular to sub-rounded quartz, alkali feldspars with clay and iron-oxide coatings. The sediments geochemical composition is essentially silica, alumina and iron oxide. Toxic trace elements including Cd and Pb occur in very minor to insignificant concentrations with Igeo (index of geo-accumulation) values classifying the sediments as unpolluted. The sediments are also characterised by variably-high CIA (chemical index of alteration) values (av. 60) which is an indication that their derivation was from moderate to high tropical weathered source areas.

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 score0.012
Threshold uncertainty score0.023

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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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Same venueFountain Journal of Natural and Applied SciencesSame topicMine drainage and remediation techniquesFrench-language works237,207