A Study of Environmental Impacts Due to Uranium Exploration and Development in Labrador, Canada
Bibliographic record
Abstract
There are several studies on environmental contaminations due to active Uranium (U) mining and after decommissioning of U mines. However, there are very few information on environmental impacts due to U exploration and development (E&D). This lack of information hinders generating baseline data for future environmental health impact assessment, particularly during the active phase of mining. We conducted an extensive environmental sampling around a U E&D site in Labrador in 2013. We collected soil, water, sediment, leaves of wild plants and trees (Carex Aquatilis, Myrice Gale, Spruce and Alder), tree core (Spruce), and fish (Trout) samples. We also collected similar samples from control sites from a nearby area. The rationale behind the sampling was to explore the level of contamination and impacts on food chain, as local Aboriginal (Inuit) community frequently visit those sites for hunting, catching fish and collection of traditional foods like berries. We found very high level of U contamination (10 to 250 times more than the control sites) of water, sediments and plant samples from the actual E&D site. Mixture of stream water from the surrounding forest further diluted the contaminated water. Therefore, the level of contamination drastically fell beyond few hundred meters of E&D site. The E&D site is almost 25km from the nearest community. It showed that until now the contamination is still localized. As of now there is no immediate threat to human health; however the local authority should erect a fence around the highly contaminated site to prevent any animal contamination. Due to growing global demand for U, the E&D site will turn into fully functioning U mining in near future. The study has generated very rich baseline data for future environmental health impact assessment.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".