Education and Training in Radiation Protection and Mutual Recognition of Qualification in Australia, Canada, News Zealand, Germany and UK
Bibliographic record
Abstract
Radiation therapy plays an important role in the management of various cancers. However, it is equally important to keep radiation levels as low as reasonably achievable to protect radiation staff and general public from harmful effects of radiation. This requires implementation of good radiation protection practices at all times which in turn requires good training and knowledge in radiation protection issues. Radiation is used in various sectors such as nuclear, medical and research and the expertise in radiation protection is on decline. Thus maintaining excellent radiation protection practices and competencies is essential in ensuring safe use of ionizing radiation. More over there is lack of mutual recognition of qualified experts across many countries of the world. This paper discovers education and training approaches employed for Radiation protection training for qualified experts (Radiation protection experts, Radiation Protection officers, Radiation protection supervisors and Radiation protection advisors) in Australia, New Zealand, Canada, UK and Germany with respect to medical sector especially radiation oncology and radiotherapy.This study also assesses whether mutual recognition of training across these countries exist or not. The study also assesses what is equivalent to what and who can do what. This will assist in harmonizing and standardization of training in these countries as well as will help in establishing infrastructure for mutual recognition of training for Radiation Protection Experts. This in turn will guarantee fast movement of skilled workers. The process of harmonization of radiation protection training has already started in Europe and by expanding this process to Australia, Canada and New Zealand will eventually help in developing a compatible system of radiation protection training and expertise across these countries which in turn will help in establishing international standardization of radiation protection training. Moreover, it will help tackle decline in radiation protection expertise and will ensure availability of excellent radiation protection knowledge and skills which can meet demands of the future. This is unique research in the sense that it has not been carried out in Canada, Australia and New Zealand.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".