International Intercomparison of Emergency Radiation Monitoring Techniques Via Coordinated Field Exercise
Bibliographic record
Abstract
To evaluate the emergency radiation monitoring capabilities of various countries, a coordinated field exercise involving Japan, France, the Republic of Korea, and Canada was conducted near the Fukushima Daiichi Nuclear Power Sation. Under standardized conditions, manborne, carborne, and airborne surveys were performed using different detector systems to assess ambient dose equivalent rates (air dose rates). JAEA employed$\text{CsI}(\text{TI})$detectors for manborne and carborne surveys, and$\text{LaBr}_{3}(\text{Ce})$scintillation detectors for airborne surveys using an unmanned helicopter. Despite differences in equipment and analysis methods, all teams observed consistent trends in air dose rate distributions. Although airborne surveys had lower spatial resolution and showed elevated dose rates due to the influence of surrounding terrain, they effectively covered areas inaccessible from the ground. These results demonstrate the feasibility of producing internationally comparable dose rate maps and emphasize key factors such as shielding and energy response in dose rate assessments. The exercise reaffirmed the importance of harmonized protocols and international collaboration in nuclear emergency response.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".