Potential ecological risk from heavy metals in surface sediment of lotic systems in central region Peru
Bibliographic record
Abstract
High Andean rivers are fragile ecosystems in the face of various threats, including heavy metal contamination. The objective of this study was to evaluate the potential ecological risk of heavy metals in surface sediment of lotic systems in the central region of Peru. Composite samples of surface sediments were collected from the Chía and Miraflores rivers and the concentrations of heavy metals were determined. The ecological risk analysis was carried out based on the contamination indexes and confirmed by the modified degree of contamination (mCd). The concentration of heavy metals in the sediment of the Chía river was in the following descending order: Fe > Mn > Zn > V > Pb > Cr > Ni > Cu > Mo > Hg, y en el río Miraflores fue: Fe > Mn > Zn > Ni > V > Cr > Cu > Pb > Hg > Mo. The mean concentration of Cu, Cr, Fe, Mn, Mo, Ni, Pb, and V in the sediment samples in both rivers did not exceed the threshold values of the continental crust concentration, nor the interim sediment quality guidelines of the Canadian Council of Ministers of the Environment. However, the mean concentration of Hg exceeded the guideline values in the Miraflores river and the likely effect (0.7 mg.kg−1) adverse effects. The values of the enrichment factor (EF), contamination factor (CF), geoaccumulation index (Igeo), and pollution load index (PLI) indicated low contamination in the sediments of the rivers studied, being confirmed by the modified degree of contamination (mCd). Finally, the risk assessment showed that heavy metals in the sediments presented a low potential ecological risk.
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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) | 0.000 | 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 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".