Impact of historical gold mining activities on marine sediments in Wine Harbour, Nova Scotia, Canada
Bibliographic record
Abstract
Past investigations at historical gold (Au) districts in Nova Scotia, Canada have identified elevated concentrations of arsenic (As) and mercury (Hg) in nearby sediments and waters. These metal(loid)s are derived from erosion of mineralized bedrock, and the disposal of mine tailings into the environment during early operations. The Wine Harbour gold district is located along the eastern shore of Nova Scotia, and produced 1329 kg of Au from 75 581 tonnes of crushed rock from 1862 to 1939.The gold occurs in arsenopyrite-bearing quartz-carbonate veins and was extracted using stamp milling and Hg amalgamation. Historical maps document tailings deposits near former stamp mill sites; however, the extent to which these mine wastes influence environmental quality in the adjacent marine environment is uncertain. In this study, we measured metal(loid) concentrations in tailings, marine sediments, and surface waters to assess the lateral and vertical extent of mining-related impacts on Wine Harbour. Chemical analyses of terrestrial and intertidal tailings reveal high concentrations of both As (86–196 000 mg/kg) and Hg (444–320 000 µg/kg). Analyses of marine sediments show a wide range in both As (4–568 mg/kg) and Hg (<5–7430 µg/kg) concentrations. In general, the highest metal(loid) concentrations in sediments were recorded down-gradient of stamp mill sites. Elevated concentrations were also detected in sediments underlying an active mussel aquaculture operation at the western end of the harbour. Results from this study have been used to help assess potential ecosystem and human health risks associated with historical gold mine wastes in the Wine Harbour area.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".