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Record W2326561635 · doi:10.9790/2402-081235357

Pollution Status of Metals in Sediments from Ikere, Iseyin, Opeki, Ofiki and Igangan Sections of the Ogun River Basin

2014· article· en· W2326561635 on OpenAlexaboutno aff
Anslem Diayi, A. M. Gbadebo

Bibliographic record

VenueIOSR Journal of Environmental Science Toxicology and Food Technology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsOgun statePollutionEnvironmental scienceHeavy metalsSedimentDrainage basinStructural basinGeologyEnvironmental chemistryHydrology (agriculture)GeochemistryGeographyArchaeologyGeomorphologyChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

Sediments were obtained from sections of the Ogun River namely Ikere, Iseyin, Opeki, Ofiki and Igangan. Layers of sediment ranging from 0-5cm, 5-10cm and 10-15cm were obtained after which they were air dried, pulverized and sieved using a 2mm sieve to obtain very fine grain particles for analysis. The sediments were then subjected to physicochemical analysis in which pH and conductivity were determined using standard methods by the American Public Health Association of 1992 while Organic Carbon was determined by Wakley Method. For the sediment metal analysis, sediments were subjected to the Induced Couple Plasma/Mass Spectrometer (ICP/MS) analysis. Results obtained were then used for the calculation of the Geochemical Pollution Intensity (Igeo). Metal results obtained showed that all metals had concentrations lower than Environment Canada Sediment Quality Guideline standards of 35.70ppm, 35.00ppm, 0.60ppm, 123.00ppm, 5.90 ppm, 0.17ppm and 37.50ppm for Cu, Pb, As, Zn, Hg, Cd, and Cr respectively except that of Pb obtained from Opeki 0-5cm with value of 80.80ppm which was higher than the 35.00 ppm standard limit. Thus, this sediment layer requires frequent monitoring as toxic levels of Pb can be harmful to sediment/aquatic species. All Igeo values showed unpolluted status for the metals analyzed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.235
Teacher spread0.225 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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