Tracing Mercury Contamination from the Idrija Mining Region (Slovenia) to the Gulf of Trieste Using Hg Isotope Ratio Measurements
Bibliographic record
Abstract
To demonstrate the power of precise isotope ratio measurements of Hg in environmental samples and, more particularly, to test the use of stable isotopes as distinct tracers of the contamination source, we investigated a well-documented system, the Hg mining region near Idrija, Slovenia. Sediments alongside the Idrijca River, the Soca/Isonzo River, and in the Gulf of Trieste were analyzed to determine the variation in Hg isotopic composition versus distance from the source. Similar Hg isotopic signatures were observed among samples collected from the rivers Idrijca, Soca/Isonzo, and around the river mouth in the Gulf of Trieste, suggesting that sediments throughout the watershed of the Soca/Isonzo River to the Gulf of Trieste are dominated by Hg exported from the headwaters of the Idrijca River. Only locations on the southern part of the gulf, outside the river plume, showed lower values of the isotopic composition comparable to the Hg isotopic signature of Adriatic Sea sediments. Using a simple binary mixing-model, we could demonstrate that all samples investigated in this study were a result of variable proportions of Hg originating from the Idrija region (progressively decreasing from >90% in the northern partto <50% in the southern gulf) and from the Adriatic Sea. These results are, so far, the first evidence that tracking of mercury sources in natural systems using mercury stable isotope ratios is feasible.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".