Selection of the most appropriate two-dosemeter algorithm for estimating effective dose equivalent during maintenance periods in Korean Nuclear Power Plants
Bibliographic record
Abstract
The application of a two-dosemeter system with its algorithm, as well as a test of its use in an inhomogeneous high-radiation field, is described in this study. The goal was to improve the method for estimating the effective dose equivalent during maintenance periods at Korean Nuclear Power Plants (NPPs). The use of this method in Korean and international NPPs, including those NPPs in the USA and Canada, was also investigated. The algorithms used by the the American National Standards Institute, Lakshmanan, the National Council on Radiation Protection and Measurements (NCRP), the Electric Power Research Institute and Kim were extensively analysed as two-dosemeter algorithms. Their possible application to NPPs was evaluated using data for each algorithm from two-dosemeter results that were obtained from an inhomogeneous high-radiation field during maintenance periods at Korean NPPs. The NCRP algorithm (55:50) was selected as an optimal two-dosemeter algorithm for Korean NPPs by taking into account the field test results and the convenience of wearing two dosemeters.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".