Geochemical Pollution Assessment of Sediment Metal from Lower Region of the Ogun River, Nigeria
Bibliographic record
Abstract
From depths of 0-5 cm, 5-10 cm and 10-15 cm, sediment samples were collected from three locations in the lower region of the Ogun River Basin, namely Mokoloki, Oke-Oko and Kara. The samples were obtained using Van Veen sediment grab after which they were stored in well labeled polythene bags for onward transportation to the laboratory. For pH and conductivity, samples were determined in-situ using standard methods by the American Public Health Association of 1992 while Organic Carbon was determined by the Wakley Method. The sediments were then air dried before analysis for particle size and metal concentration. Induced Couple Plasma Mass Spectrometry (ICP/MS) was used to determine metal concentrations. Data obtained were used to determine the geochemical pollution intensities for the various sediment samples. The results of physicochemical analyses revealed all sediment samples to be alkaline, while particle size analysis showed that the sediments were sandy. All metal concentrations for Cu, Pb, As, Zn, Hg, Cd, and Cr were lower than the Environment Canada Sediment Quality Guideline standards of 35.70 ppm, 35.00 ppm, 0.60 ppm, 123.00 ppm, 5.90 ppm, 0.17 ppm and 37.50 ppm, respectively. The low metal concen-trationsobtained from the trace metal analyses were confirmed with an ‘unpolluted status’ obtained for all sediment samples analyzed using the geochemical accumulation index formula. Results showed that metal concentrations in these areas are low and do not pose a threat to the survival of living organisms living in sediments or the surrounding environment.
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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".