Analysis and human health evaluation of trace metals and polycyclic aromatic hydrocarbons in Ocimum basilicum and Vernonia amygdalina cultivated close to industrial markets in Owerri, Imo State
Bibliographic record
Abstract
This study evaluated the presence of polycyclic aromatic hydrocarbons (PAHs) and trace metals in Vernonia amygdalina and Ocimum basilicum leaves grown near Ekeonunwa, Relief, and Toronto industrial markets in Owerri. High-performance liquid chromatography (HPLC) and Inductively Coupled Plasma Optical Emission Spectrophotometry (ICP-OES) were employed for analysis, with Cold Vapour Atomic Fluorescence Spectrophotometry (CV-AFS) specifically for mercury detection. PAH Concentrations (mg kg −1 PAHs): V. amygdalina : Ekeonunwa (5.56), Relief (8.99), Toronto (0.13) O. basilicum : Ekeonunwa (7.18), Relief (3.37), Toronto (0.17), while The average levels of metals in the soil samples ranked in descending order as follows: Fe > Mn > Zn > Cu > Al > Cd > Pb > Cr > Co > V > Li > Hg, while those in the vegetable samples followed the sequence: Fe > Mn > Zn > Cu > Al > Pb > Cd > Cr > V > Co > Li > Hg. Average metal concentrations were higher than FAO/WHO maximum permissible limits. Estimated Daily Intake (EDI) values for all metals were lower than their respective Reference Doses (RfD), Health Risk Index (HRI), Target Hazard Quotient (THQ), and Hazard Index (HI) values for both vegetables were significantly below 1, suggesting minimal risk from metal exposure. However, Target Cancer Risk (TCR) and Cumulative Target Cancer Risk (CTCR) assessments indicated a potential elevated cancer risk for individuals consuming these vegetables from areas where risk thresholds were surpassed. Preventative measures are recommended in these specific locations.
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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 | 0.000 | 0.000 |
| 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".