Proceedings of international symposium of trends in radiopharmaceuticals 2023 (ISTR-2023)
Bibliographic record
Abstract
The International Atomic Energy Agency (IAEA) held the 3rd International Symposium on Trends in Radiopharmaceuticals, (ISTR-2023) at IAEA Headquarters in Vienna, Austria, during the week of 16-21 April 2023. This procedural paper summarizes highlights from symposium presentations, posters, panel discussions and satellite meetings, and provides additional resources that may be useful to researchers working with diagnostic and therapeutic radiopharmaceuticals in the academic, government and industry setting amongst IAEA Member States and beyond. More than 550 participants in person from 88 Member States attended the ISTR-2023. Over 360 abstracts were presented from all over the world by a diverse group of global scientists working with radiopharmaceuticals. Given this group of international radiochemists is unique to ISTR (IAEA funding enabled many to attend), there was an invaluable wealth of knowledge on the global state of the radiopharmaceutical sciences present at the meeting. The intent of this Proceedings paper is to share this snapshot from our international colleagues with the broader radiopharmaceutical sciences community by highlighting presentations from the conference on the following topics: Isotope Production and Radiochemistry, Industrial Insights, Regional Trends, Training and Education, Women in the Radiopharmaceutical Sciences, and Future Perspectives and New Initiatives. The authors of this paper are employees of IAEA, members of the ISTR-2023 Organizing Committee and/or members of the EJNMMI Radiopharmacy and Chemistry Editorial Board who attended ISTR-2023. Overall, ISTR-2023 fostered the successful exchange of scientific ideas around every aspect of the radiopharmaceutical sciences. It was well attended by a diverse mix of radiopharmaceutical scientists from all over the world, and the oral and poster presentations provided a valuable update on the current state-of-the-art of the field amongst IAEA Member States. Presentations as well as networking amongst the attendees resulted in extensive knowledge transfer amongst the various stakeholders representing 88 IAEA Member States. This was considered particularly valuable for attendees from Member States where nuclear medicine and the radiopharmaceutical sciences are still relatively new. Since the goal is for the symposium series to be held every four years; the next one is anticipated to take place in 2027.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.108 | 0.050 |
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".