Human mercury exposure and adverse health effects in the Amazon: a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines issues of human mercury (Hg) exposure and adverse health effects throughout the Amazon region. An extensive review was conducted using bibliographic indexes as well as secondary sources. There are several sources of Hg (mining, deforestation, reservoirs), and exposure takes place through inhalation or from fish consumption. There is a wide range of exposure, with mean hair-Hg levels above 15 microg/g in several Amazonian communities, placing them among the highest reported levels in the world today. Dietary Hg intake has been estimated in the vicinity of 1-2 microg/kg/day, considerably higher than the USEPA RfD of 0.1 microg/kg/day or the World Health Organization recommendation of 0.23 microg/kg/day. Neurobehavioral deficits and, in some cases, clinical signs have been reported both for adults and children in relation to Hg exposure in several Amazonian countries. There is also some evidence of cytogenetic damage, immune alterations, and cardiovascular toxicity. Since fish provide a highly nutritious food source, there is an urgent need to find realistic and feasible solutions that will reduce exposure and toxic risk, while maintaining healthy traditional dietary habits and preserving this unique biodiversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it