A Review Of Mercury in Lake Victoria, East Africa: Implications for Human and Ecosystem Health
Bibliographic record
Abstract
Lake Victoria, East Africa, has been the site of many recent studies measuring mercury (Hg) concentrations in water, fish, sediment, soil, and humans. Most of these studies were motivated by concerns about Hg contamination from processing of gold ore on the southern shores. Total Hg (THg) concentrations in fish were usually below permissible World Health Organization (WHO) concentrations and international marketing limits and do not threaten the lucrative export industry. Nile perch 3-10 kg and most >10 kg had THg concentrations above the WHO threshold concentrations for at-risk groups (200 ng/g). Elevated THg concentrations in large Nile perch are not of major concern because Nile perch are rarely consumed by the people living on Lake Victoria and very large Nile perch are becoming increasingly rare in catches. Water THg concentrations were below Canadian drinking water guidelines but were elevated relative to those in the northern Great Lakes. Sediment and soil THg concentrations were within inter-national guidelines and are comparable to those in northern latitudes but are lower than those in the Amazon basin. Biomass burning and soil erosion are estimated to be the major sources of THg for the lake and probably constitute a larger source of THg than gold mining in Tanzania.THg concentrations in urine and hair from human volunteers indicate that while gold miners and frequent skin-bleaching cream users are at risk of inorganic mercury poisoning, the rest of the population, including fishermen, is not. Human exposure assessments demonstrated that fish consumption and soil geophagy constitute major sources of THg for humans, but the total estimated daily intake of THg was below the Health Canada tolerable daily intake (TDI) limits. The use of beauty creams containing high inorganic Hg concentrations, however, caused the estimated THg exposure to exceed the TDI. The high THg content in the hair of regular cream users supports this assessment. The nutritional benefits of fish and soil geophagy outweigh the risk of THg poisoning. Still, due to the importance of those natural items as a THg source to humans, as well as the changing nature of Lake Victoria, regular monitoring and risk assessments need to be carried out in the Lake Victoria catchment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".