Trace Metal Enrichment in Sediments from Otofure and Teboga Waste Dump Sites in Benin City, Nigeria
Bibliographic record
Abstract
Analyses of lead, copper, chromium, cadmium, nickel, zinc and manganese contents in Otofure and Teboga waste dumps in Benin City, Nigeria were carried out to determine trace metal enrichment and distribution in the soils around the dump sites and environs. Results of analyses show that trace metal concentrations in the waste dumps were greater than those from the reference background sites by magnitude concentration differences of Pb (18.711 mgkg-1), Cu (12.342 mgkg-1), Cr (0.073 mgkg-1), Cd (0.908 mgkg-1), Zn (104.669 mgkg-1), Ni (3.522 mgkg-1), Mn (203.803 mgkg-1) in Otofure area; and Pb (3.522 mgkg-1), Cu (10.466 mgkg-1), Cr (0.556 mgkg-1), Cd (1.026 mgkg-1), Zn (109.026 mgkg-1), Ni (4.307 mgkg-1) and Mn (161.349 mgkg-1) in Teboga area. The calculated contamination/pollution (C/P) index values show that the dump sites were slightly polluted while the reference sites showed insignificant contamination. Analysis of enrichment factor shows that the dump sites are enriched in lead and zinc, and these decreased with distance away from the waste dump sites. The geochemical association of Cr–Cu–Zn in the soil among others shows their inclination towards anthropogenic sources. This study shows slight metal enrichment in lead and zinc content over other metals studied, but generally the average concentrations of trace metals were below international guideline values for environmental quality criteria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".