Lead isotope ratios as a tracer for lead contamination sources: A lake Andong case study
Bibliographic record
Abstract
The objective of this study was to evaluate stable Pb isotope signatures as a tracer for Pb contamination in Lake Andong. For Pb isotope analysis, we collected water and sediment from Lake Andong, particles in the air, soils, and stream water, mine tailings, sludge and wastewater from zinc smelting around lake Andong watershed. The results showed that Pb isotope ratios (206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb) for zinc concentrate were 18.809 ± 0.322, 15.650 ± 0.062, and 38.728 ± 0.421, respectively. In wastewater, isotopic ratio values (206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb) were 17.363 ± 0.133, 15.550 ± 0.025, and 37.217 ± 0.092, respectively. Additionally, isotopic ratio values (206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb) for sludge were 17.515 ± 0.155, 15.537 ± 0.018, and 37.357 ± 0.173, respectively. These values were similar to those in zinc and lead concentrate originated from Canada and South America. In contrast, Pb isotope ratios of soil, tailings and sediment from Lake Andong were similar to those of Korean ore. Atmospheric particles showed different patterns of Pb isotope ratios from sediments, soils, and zinc smelting and this needs further investigation in order to identify atmospheric Pb sources.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".