Regional hydrogeochemical mapping in Central Chile: natural and anthropogenic sources of elements and compounds
Bibliographic record
Abstract
Geochemistry is a key tool in identifying sources of elements for both mineral exploration and environmental purposes. This study evaluates the first systematic regional hydrogeochemical survey for environmental assessments of the classic Andean copper mineral province and the Andina–Los Bronces mining district of Central Chile. One hundred and forty-five water samples were collected systematically in the Valparaíso and Metropolitana Regions of Central Chile, including the capital, Santiago. The concentrations of more than 70 elements and compounds were determined using inductively coupled plasma mass spectrometry (ICP-MS) and ion chromatography (IC) along with the stable isotopes (δD, δ 18 O, δ 34 S, δ 18 O SO4 , δ 15 N and δ 18 O NO3 ) and used to define the geochemical baselines in the area and distinguish between different sources. The geochemistry demonstrates the potential to distinguish between natural (bedrock, hydrothermal alteration and mineralization) and anthropogenic (agriculture, sewage and urban) sources of elements. The distribution patterns of many chemicals show a strong correlation with the presence of evaporitic components (Ca, SO 4 2- , Sr, K, Rb, total dissolved solids (TDS)), hydrothermal alteration and sulphide mineralization (Cu, Zn, Ni, Cd, Co and REEs). High concentrations of nitrate, phosphate and alkalinity occur downstream of agricultural areas and reflect pollution from fertilizers. Overall, the catchment areas affected by mining activities are relatively small and highly localized compared to those affected by agriculture and urban centres. Supplementary material: A list of anomalously high element concentrations and specific isotopic compositions associated by source is available at: http://www.geolsoc.org.uk/SUP18799
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".