Increased human health risks at a legacy mine site: copper and lead bioaccessibility of oxidised tailings
Bibliographic record
Abstract
With climate change, conditions for dust generation are expected to be more prevalent. A potential dust source of concern are mine wastes due to the likelihood of potentially toxic elements which pose a human health risk if ingested or inhaled. This study analysed sieved mine tailings from a legacy mine in Nova Scotia, Canada. The aim of the research was to analyse total concentrations of Cu and Pb in tailings samples sieved to represent dust; to determine gastric bioaccessibility of Cu and Pb in these samples; and to analyse the impact of mineralogy on Cu and Pb bioaccessibility. Mineralogy was determined with a scanning electron microscope and automated mineralogy software. Tailings were sampled from an uncovered, subaerial, tailings impoundment. Copper bioaccessibility had a strong positive correlation with carbonate and oxide copper hosts. Lead bioaccessibility had a strong positive correlation to one oxidation product, cerussite (lead carbonate). Lead was predominantly hosted in cerussite and had greater bioaccessibility than copper which was predominantly hosted in chalcopyrite. The results highlight the increased human-health risk posed by subaerial tailings at an abandoned mine.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".