Near Term and Promising Long Term Options for the Deployment of Thorium Based Nuclear Energy
Bibliographic record
Abstract
There has been an interest among Member States in the use of the thorium fuel cycle to address the sustainable growth of nuclear energy. Thorium based fuels have been studied for their potential applications in almost all types of reactor, including water cooled reactors, high temperature reactors, fast reactors and molten salt reactors, albeit on a smaller scale than uranium and uranium–plutonium fuels. Thorium has several inherent physical and neutronic characteristics that may be exploited in current and next generation nuclear energy systems to achieve, for example, enhanced capabilities for high conversion, further augmented inherent safety characteristics and reduced minor actinides production. Some Member States view near to medium term deployment of thorium fuels in proven reactor types as not only feasible, but also attractive in meeting expanding energy needs. Several options are also currently under consideration or active development for deployment in the longer term. On the suggestion of the Technical Working Group on Fuel Performance and Technology, in 2011 the IAEA launched a coordinated research project entitled Near Term and Promising Long Term Options for the Deployment of Thorium Based Nuclear Energy. This research project provided a platform for sharing research results and previous experiences among national laboratories and research institutes of participating Member States. The need for coordinated examination of how thorium fuel types may be deployed and what hinders progress towards such goals was addressed by the project to develop strategies for the timely deployment of thorium based nuclear energy systems that can serve as a component of the global energy supply. Canada, China, Czech Republic, Germany, India, Italy, Switzerland, the United Kingdom and the United States of America all participated in the coordinated research project; this publication is an outcome of the project.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".