Key outcome summaries of the scientific programme of the IRPA15 congress
Bibliographic record
Abstract
This special issue of JRP includes a selection of research papers and review articles presented at the 15th Congress of the International Radiation Protection Association (IRPA15) as chosen by the scientific committee. All invited journal contributions are suitably expanded beyond the initial conference presentations to meet the criteria for a full journal article and include (a) presentation within a comprehensive radiological protection context and (b) additional data/interpretation. Published contributions address a wide spectrum of scientific topics and concepts to further develop the radiation protection (RP) system. They are based on scientific evidence and available experience in a wide spectrum of applications of the protection system. The IRPA is the international voice of the RP profession. It promotes excellence in RP by providing benchmarks of good practice, enhancing professional competence, and encourages the application of the highest standards of professional conduct, skills and knowledge for the benefit of individuals and society. Within the overarching theme of the conference 'Bridging RP Culture and Science-Widening Public Empathy' IRPA15 provided an invaluable opportunity to discuss and strengthen the relations between RP culture and science, and share developing scientific knowledge and related experience in RP among members of the scientific community, between representatives of key international organizations, including ICRP, IAEA, WHO, and NEA but also with the public. Some discussions focused on the rationale of available RP programmes and priorities, with an opportunity to identify and further develop key scientific issues of the current RP system as well as key processes for the interaction between members of the scientific community and society. The scientific programme of IRPA15 included eight topics and four thematic areas. The topical areas were: Underpinning Science; Dosimetry and Measurement; the System of Protection; Standards and Regulation; Practical Implementation-Medical Sector, as well as Industry and Research; Emergency Preparedness and Response; Existing Exposures and Non-ionizing Radiation. The thematic areas addressed were: Ethics; Communication and Public Understanding; RP Culture; Human Capital and Competency.
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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.203 | 0.124 |
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".