Environmental Risk Assessment Based on High-Resolution Spatial Maps of Potentially Toxic Elements Sampled on Stream Sediments of Santiago, Cape Verde
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Bibliographic record
Abstract
Geochemical mapping is the base knowledge to identify the regions of the planet with critical contents of potentially toxic elements from either natural or anthropogenic sources. Sediments, soils and waters are the vehicles which link the inorganic environment to life through the supply of essential macro and micro nutrients. The chemical composition of surface geological materials may cause metabolic changes which may favor the occurrence of endemic diseases in humans. In order to better understand the relationships between environmental geochemistry and public health, we present environmental risk maps of some harmful elements (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn) in the stream sediments of Santiago, Cape Verde, identifying the potentially harmful areas in this island. The Estimated Background Values (EBV) of Cd, Co, Cr, Ni and V were found to be above the Canadian guidelines for any type of use of stream sediments and also above the target values of the Dutch and United States guidelines. The Probably Effect Concentrations (PEC), above which harmful effects are likely in sediment dwelling organisms, were found for Cr and Ni. Some associations between the geological formations of the island and the composition of stream sediments were identified and confirmed by descriptive statistics and by Principal Component Analysis (PCA). The EBV spatial distribution of the metals and the results of PCA allowed us to establish relationships between the EBV maps and the geological formations. The first two PCA modes indicate that heavy metals in Santiago stream sediments are mainly originated from weathering of underlying bedrocks. The first metal association (Co, V, Cr, and Mn; first PCA mode) consists of elements enriched in basic rocks and compatible elements. The second association of variables (Zn and Cd as opposed to Ni; second PCA mode) appears to be strongly controlled by the composition of alkaline volcanic rocks and pyroclastic rocks. So, the second PCA mode is also considered as a natural lithogenic mode. The third association (Cu and Pb; third PCA mode) consists of elements of anthropogenic origin.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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