An Internal Tritium Concentration Analysis in Urine Samples as a Function of Submission Time after Airborne Tritium Intake at Korean Pressurized Heavy Water Reactors
Bibliographic record
Abstract
In pressurized heavy water reactors, workers who enter radiation controlled areas must submit their urine samples to health physicists after radiation work; these samples are then used to monitor internal radiation exposure from tritium intake. This procedure assumes that the samples submitted represent tritium concentration inside the body at equilibrium. According to both technical reports from the International Commission on Radiological Protection and experimental results from Canadian nuclear utilities, tritium inside the body generally reaches equilibrium concentration after approximately 2-3 hours of intake. In practice, urine samples can be submitted either before the 2 hours mark or after several hours of radiation work because of the numerous tasks that workers must perform and their frequent entries during nuclear power plant maintenance. In this paper, tritium concentration in workers' urine samples was measured as a function of time submitted after radiation work. Based on the measurement results, changes in the tritium concentration inside the body and its effect on internal dose assessment were then analyzed. As a result, it was found that tritium concentration reaches equilibrium concentration before the 2 hours mark for most workers' urine samples.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".