Ecological and public health estimations of potentially toxic elements in soils from an abandoned dumpsite in a tropical climatic zone
Bibliographic record
Abstract
The presence of toxic elements in soils at abandoned dumpsites poses significant ecological and health risks, especially in regions where climatic conditions influence contaminant dispersion and persistence. This study examined the concentrations of Al, As, Ba, Cd, Co, Cr, Cu, Fe, Hg, K, Mn, Mo, Na, Ni, Pb, Si, Ti and Zn in soil samples from the Aboabo abandoned dumpsite using inductively coupled plasma mass spectrometry. Results indicated that apart from Sr, whose mean concentration exceeded the WHO/FAO and Canadian guideline levels, the other elements were found within the established ranges. Ecological indices-including the contamination factor, enrichment factor, and geoaccumulation index-classified As, Cd, Cr, Co, Hg, Ni, Pb, and Zn as exhibiting low contamination, little enrichment, and being largely uncontaminated. However, Sr showed moderate to substantial contamination based on these indices. Despite this, the potential ecological risk index and the pollution load index suggested an overall low ecological risk. Health risk assessments indicated that both adults and children are unlikely to experience non-carcinogenic effects. However, children may be at potential risk of carcinogenic effects from the selected elements at the abandoned dumpsite. These findings provide baseline data on soil contamination at the site and underscore the need for continued management of abandoned dumpsites.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".