Radiological protection in North American naturally occurring radioactive material industries
Bibliographic record
Abstract
All soils and rocks contain naturally occurring radioactive material (NORM). Many ores and raw materials contain relatively high levels of natural radionuclides, and processing such materials can further increase the concentrations of natural radionuclides, sometimes referred to as 'technologically enhanced naturally occurring radioactive material' (TENORM). Examples of NORM minerals include uranium ores, monazite (a source of rare earth minerals), and phosphate rock used to produce phosphate fertiliser. Such activities have the potential to result in above background radiation exposure to workers and the public. The objective of this paper is to review the sources and exposure from NORM in North American industries, and provide a perspective on the potential radiological hazards to workers and the environment. Proper consideration of NORM issues is important and needs to be integrated in the assessment of these projects. Concerns over radioactivity and radiation amongst non-governmental organisations and the local public have resulted in the cancellation of NORM mining and mineral extraction projects, as well as inhibition of the safe use of by-product materials from various NORM industries. This paper also briefly comments on the current regulatory framework for NORM (TENORM) in Canada and the USA, as well as the potential implications of the recent activities of the International Commission on Radiological Protection for NORM industries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".