Impacts of the Covid-19 on the IRPA young generation activities in radiation protection: testimonies and experience feedback
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The measures implemented to limit the spread of Covid-19 have brought many challenges on the work organization, the radiation protection being no exception. The IRPA Young Generation Network has investigated through a collection of testimonies the impacts of these measures and how the continuity and consistency of radiation protection was ensured. This article presents the results of the analysis of the testimonies. The impacts of the Covid-19 for each of the radiation protection related sectors covered by the survey are presented from a young generation perspective. The impacts are never negligible and even more important in some sectors and for some type of work. The adaptations made to the radiation protection and how they were implemented are shown, as well as the lessons-learned from these unprecedented circumstances.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it