Bioaccumulation of contaminants in amphibians in historical gold mining areas of Nova Scotia
Bibliographic record
Abstract
Nova Scotia has a long history of gold mining dating back to the mid-1800’s. Early \nmining techniques depended on the use of liquid mercury (Hg). As there were little or no \nenvironmental regulations at the time, over 3,000,000 tonnes of mine waste (tailings) were \nreleased into the environment. These tailings can contain high concentrations of toxic chemicals \nincluding Hg and arsenic (As). Such chemicals have negative effects on the environment and on \nwildlife. Frogs are often used as indicators of environmental conditions. Their thin, permeable \nskin and semi-aquatic lifestyle can lead to the bioaccumulation of toxins in frog tissues. This \nstudy compares bioaccumulation of Hg in frogs collected from six research sites and one \nreference site from within historical gold mining districts in Nova Scotia, Canada. Dried, ground \nfrog-leg tissues were analyzed for Hg content using a Milestone DMA 80 direct mercury \nanalyzer. This project tests the hypothesis that if concentrations of Hg are high at research sites \nidentified as legacy tailing areas in Nova Scotia, then the concentrations of total mercury content \n(THg) in the tissues of amphibians collected at the respective sites will also be high. Adult \namphibians sampled from contaminated sites had concentrations of THg ranging from 0.1324 - \n2.1329 mg/kg. Tadpoles sampled from contaminated sites had concentrations of THg ranging \nfrom 0.1384 -15.9412 mg/kg. The THg concentrations in adult amphibians at a reference site \nranged from 1.664 – 2.3959 mg/kg. The THg concentrations in tadpoles at the reference site \nranged from 0.0494 – 3.3312 mg/kg. These ranges indicate elevated Hg levels in both adult \namphibians and tadpoles. This project, as part of the legacy gold mine contaminants research led \nby the Dynamic Environment and Ecosystems Health Research (DEEHR) team at Saint Mary’s \nUniversity will enhance the understanding of impacts of historical human activity on aquatic \necosystems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".