CHEST WALL THICKNESS MEASUREMENTS AND THE DOSIMETRIC IMPLICATIONS FOR MALE WORKERS IN THE URANIUM INDUSTRY
Bibliographic record
Abstract
The Human Monitoring Laboratory has measured the chest wall thickness and adipose mass fraction of a group of workers at a Canadian uranium refinery, a conversion plant, and a fuel fabrication site using ultrasound. A site-specific biometric equation has been developed for these workers, who seem to be somewhat larger than other workers reported in the literature. Chest wall thickness is a very important modifier on lung counting efficiency and these data have been put into the perspective of the impending Canadian dose limits that will reduce the limit of occupationally exposed workers to 100 mSv in a 5-y period with a maximum of 50 mSv in any one year. The sensitivity of the germanium and phoswich based lung counting systems have been compared. Over a range of chest wall thickness of 1.6 cm to 6.0 cm and using a 30-min counting time, the achievable MDA's lie in the range of 6.7 mg to 19.1 mg or 6.7 mg to 30 mg with a two-phoswich-detector array or a germanium lung counting system, respectively. Depending on chest wall thickness, these achievable MDA's are close to, or exceed, the predicted amounts of natural uranium that will remain in the lung (absorption type M and S) after an intake equivalent to the Annual Limit on Intake that corresponds to 20 mSv. Neither system is sufficiently sensitive to detect an intake of Type S natural uranium in a worker with a chest wall thickness that corresponds to the average (3.73 cm) if it occurred more than 7 d prior to the lung count.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".