Use of group monitoring data in lung dose estimation for intakes of uranium
Bibliographic record
Abstract
This paper describes an internal dosimetry program developed for Canadian uranium processing facilities. The recently adopted recommendations of ICRP Publication 60 have made it extremely difficult to detect intakes of insoluble forms of natural uranium by in vivo methods (lung counting). A type S intake of UO2 corresponding to a 20 mSv effective dose has a lung burden that is a factor of 2-3 lower than the MDA, 6 months after the intake occurred. A new methodology, approved in principle by the Canadian Nuclear Safety Commission, has been designed to overcome this problem by summing sequential, but separate, lung counts for an individual, or summing lung counts from a group of workers performing similar tasks. This summing technique effectively increases the counting time and, therefore, reduces the MDA to a value below the dose limit. Doses will be assigned to the individual or work group based on the average lung burden.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".