A Multi-Index Analysis Approach to Heavy Metal Pollution Assessment in River Sediments in the Ponce Enríquez Area, Ecuador
Bibliographic record
Abstract
The area of Ponce Enríquez, Southern Ecuador, is one of the most important artisanal and small scale gold mining (ASGM) areas in the country, where informal mining operations can be found using amalgamation technique, even though it has been prohibited since 2010. Considering the potential impact of these mining operations, the present research focused on heavy metal pollutants in subsurface sediments at 214 sampling locations from several detailed sampling campaigns in the rivers Fermín, Fermín Norte, Guanache, Villa, and Siete. Four parameters were calculated to evaluate the geochemical composition of the river sediment and heavy metal concentrations: The enrichment factor (EF), the geo-accumulation index (Igeo), the contamination factor (Cf) and the pollution load index (PLI). The analyzed elements were Cu, Pb, Zn, Ni, As, Cd, Sb, Sr, and Hg. Due to the lack of standards for pollution levels in sediments in Ecuador, Canadian guidelines were used as interim sediment quality guidelines (ISQG) in this research for comparison with the obtained results in subsurface sediments. The multi-index geochemical analysis indicated elevated heavy metal concentrations in all subsurface sediments in the studied river ecosystems.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".