Heavy Metals of Santiago Island (Cape Verde) Alluvial Deposits: Baseline Value Maps and Human Health Risk Assessment
Bibliographic record
Abstract
The chemical composition of surface geological materials may cause metabolic changes and promote endemic diseases (e.g., oncological, gastrointestinal, neurological or cardiovascular diseases). The results of a geochemical survey is presented following the guidelines proposed by the International Project IGCP 259 performed on the alluvium of Santiago Island (Cape Verde) and focused on public health issues. Geochemical mapping is the base knowledge needed to determine critical contents of potential toxic elements and the potentially harmful regions in the planet. This work presents maps of baseline values of potentially toxic elements (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn) in Santiago alluvium and the assessment of their human health risks. According to the results the Cd, Co, Cr, Ni and V baseline values are above the Canadian guidelines for stream sediments (for any proposal use) and for soils (for agricultural and residential proposal uses) and also above the target values of Dutch guidelines. Hazard indexes (HI) were calculated for children and adults. For children (HI) are higher than 1 for Co, Cr and Mn, indicating potential non-carcinogenic risk. For the other elements and for adults there is no potential non-carcinogenic risk. Cancer risk was calculated for Cd, Cr and Ni exposures, for adults and children, and the results are only slightly higher than the carcinogenic target risk of 1 × 10−6 for adults exposed to Cr by inhalation. However, these results may be underestimated because alluvial contaminants may be indirectly ingested by groundwater and by crop and vegetables consumption.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".