Environmental Radioactive Impact Associated to Uranium Production
Bibliographic record
Abstract
Abstract: Problem statement: One century of uranium mining in Europe and North-America created a legacy of ore mining and milling sites needing rehabilitation for environmental and human safety. In the last decades developments of uranium mining displaced the core of this activity to Australia, Canada and African countries. In the coming years, uranium mining is expected to grow further, in those countries and elsewhere, due to the possible increase of nuclear power production and thus the amount of radioactive and toxic tailing materials will grow. Approach: International radiation protection guidelines and legislation have known recent developments and set the radiation dose limit applied to members of the public at 1 mSv y−1. Taking into account past and present uranium waste management and environmental remediation measures adopted already in some countries, we assessed the implications of enforcing this new dose limit in uranium milling and mining areas. Results: The radioactive impact of uranium mining and milling was illustrated through case studies. Environmental radioactivity monitoring and surveillance carried out in areas impacted by uranium mining and milling industry showed generally that dose limit for members of the public was exceeded. The compliance with this dose limit is nowadays the main goal for environmental remediation programs of legacy sites implemented in European Union countries. Taking into account the new radiation protection regulations, a change is required in mining practices from traditionally reactionary (problem solving) to proactive (integrated management) and life-cycle approach. Conclusion: A new paradigm in uranium mining should be implemented worldwide to ensure reduced environmental radioactivity impact current and future reduced radiation risk exposure of population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".