Cadmium pollution of water, soil, and food: a review of the current conditions and future research considerations in Latin America
Bibliographic record
Abstract
The presence of cadmium (Cd) in food produced in Latin America has been highlighted in recent years. Cadmium can be toxic to humans at low levels, and therefore monitoring its presence in food is relevant for public health. Cadmium concentrations from different sources, such as water, soil, sediment, food, and beverages were examined and discussed to address the non-occupational exposure of the Latin American population to Cd. A literature review was conducted examining publications from 2015 to 2020 and data available in the ScienceDirect and PubMed databases. Twenty-eight papers reported on Cd in water, 49 reported Cd in soil and sediments, and 86 reported on Cd in food. We have identified and discussed the factors affecting the environmental behavior and bioaccumulation of Cd, the main species used in monitoring studies, and the necessity for future research. Brazil and Mexico are the countries that provided the most available information, whereas for some countries in Central America, no information was found. The Cd levels in food examined in these studies (mostly fish and cacao) were generally below the established maximum levels, indicating a low risk. When considering the presence of Cd in food, water, and soil, Cd fractionation and chemical speciation studies are fundamental to understanding which forms of Cd are the most toxic. In turn, studies on bioaccessibility and bioavailability of Cd in food are also needed for more adequate risk assessment, but they are currently scarce within Latin America.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".