Aqueous exposure and uptake of arsenic by riverside communities affected by mining contamination in the Río Pilcomayo basin, Bolivia
Bibliographic record
Abstract
Abstract The headwaters of the Río Pilcomayo drain the Cerro Rico de Potosí precious metal-polymetallic tin deposits of southern Bolivia. Mining of these deposits has taken place for around 500 years, leading to severe contamination of the Pilcomayo's waters and sediments for at least 200 km downstream. Communities living downstream of the mines and processing mills rely on the river water for irrigation, washing and occasionally, cooking and drinking, although most communities take their drinking water from springs located in the mountains above their village. This investigation focuses on arsenic exposure in people living in riverside communities up to 150 km downstream of the source. Sampling took place in April–May 2003 (dry season) and was repeated in January–March 2004 (wet season) in five communities: El Molino, Tasapampa, Tuero Chico, Sotomayor and Cota. Cota was the control in 2003 and again in 2004; a nearby city, Sucre, and several locations in the UK were also used as controls in 2004. Drinking, irrigation and river waters, hair and urine samples were collected in each community, digested where appropriate and analysed for As using ICP-MS. Arsenic concentrations in drinking waters ranged 0.2–112 μg 1–1, irrigation water 0.6–329 μg 1–1, river waters 0.9–12,800 μg 1–1, hair 37–2110 μg kg–1 and urine 11–891 μg 1–1. All but one drinking water sample was found to contain As below the World Health Organization recommended guideline of 10 μg 1–1, although a number of irrigation and river water concentrations were above Canadian and Bolivian guidelines. Many As concentrations in the hair and urine samples from this study exceeded published values for non-occupationally exposed subjects. Analysis of mean concentration values for all media types showed that there were no statistically significant differences between the control locations and the communities exposed to known As contamination, suggesting that the source of As may not be mining-related. Arsenic concentration appears to increase as a function of age in hair samples from males and females older than 30 years. Male volunteers over the age of 35 showed increasing urine-As concentrations as a function of age, whereas the opposite was true for the females.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".