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Record W2087270293 · doi:10.5539/ijc.v7n1p55

Analysis of Heavy Metals and Some Physicochemical Parameters in Soil of Major Industrial Dumpsites in Akure Township, Ondo State of South Western Nigeria

2014· article· en· W2087270293 on OpenAlexvenueno aff
Iyabo Olabimpe Ojo, James O. Ojo, Oladele Osibanjo

Bibliographic record

VenueInternational Journal of Chemistry · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Land Suitability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryEnvironmental chemistryHeavy metalsAtomic absorption spectroscopyPollutantPositive correlationIndustrial areaPollutionOrganic matterTotal organic carbonEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Heavy metals and soil physicochemical parameters were identified as environmental pollutants in some major industrial dumpsites in Akure city of Ondo-State. The pH of the industrial dumpsites ranged from 4.87 to 6.74 with a mean value of 6.34. The organic carbon for the industrial dumpsites ranged from 0.07% to 0.97%, while the organic matter was between 0.13% and 1.68%. The concentration of Zn, Fe, Cu, Pb, Cd, Ni and Cr in µg/g in all the industrial dumpsites A, B, C ranged between 237.60 – 486.00, 174.40 – 499.20, 18.00 – 114.00, 20.60 – 249.20, 1.06 – 2.65, 30.26 – 70.58, and 30.50 – 68.08 respectively. Also the contamination/pollution index of Zn, Fe, Cu, Pb, Cd, Ni, and Cr all the industrial dumpsites. A, B, C ranged between 1.69-3.47, not detected, 0.50-3.17, 0.24-2.53, 1.33-3.23, 0.86-2.01, and 0.31-0.68 respectively Pearson Correlation indicated that Fe, Zn, Ni and Pb were highly significant (p < 0.01).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.237
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.

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

Citations7
Published2014
Admission routes1
Has abstractyes

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