Environmental Pollution by Mercury and Trace Metals in Highly Vulnerable Afro-Descendant Territories in the Department of Cauca, Colombia
Bibliographic record
Abstract
Illegal gold mining causes mercury and trace metal contamination in many Colombian territories. The government has been requested by several ethnic communities to monitor and evaluate the state of mercury contamination in strategic ecosystems. The work aimed to evaluate mercury and trace metal contamination in a mining area located in Afro-descendant communities in the department of Cauca, Colombia. The study estimated the Hg content in different environmental compartments, such as soil, water, sediments, and trees. The level of trace metals in soil samples was assessed. It also estimated the human health risk associated with Hg from fish consumption. The concentration of T-Hg was measured using atomic absorption, and the trace element content was measured using inductively coupled plasma mass spectrometry (ICP-MS). Two out of three watersheds examined had a mean T-Hg concentration in water that exceeded the international standard limit of 2.0 µg/L set by the United States Environmental Protection Agency (USEPA). The Rattlesnake River had the highest mean concentration of T-Hg in sediments at 1.05 µg/g. The community of La Toma exceeded the maximum permissible value for T-Hg in soil. While T-Hg concentrations in C. macropomum were low at 0.02 µg/g, they were surprisingly high in Prochilodus sp. at 0.53 µg/g. F. luschnathiana trees had the highest T-Hg levels at 18.3 ± 2.3 ng/g. The soil samples analyzed showed levels of As (21.4 µg/g), Cr (148.5 µg/g), V (205.0 µg/g), and Zn (146.5 µg/g) that exceeded the maximum levels established internationally. The presence of mercury and trace elements in the communities indicates a potential risk to human and environmental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".