Clean Energy Technology Observatory: Nuclear Power in the European Union - 2025 Status Report on Technology Development, Trends, Value Chains and Markets
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
Nuclear fission technology plays a crucial role in Europe's energy landscape, providing nearly a quarter of the electricity produced in the region. With approximately 100 active nuclear power reactors Europe operates almost a quarter of the global power reactors. Meanwhile, China is advancing rapidly with around 30 ongoing projects, positioning itself to soon overtake France and, eventually, the US to hold the largest nuclear reactor fleet worldwide. Similar to other areas of innovation, the market for nuclear reactors in Europe faces challenges due to persisting specific national regulator prerogatives and constraints, preventing the development of a fully integrated single market. Stakeholders are addressing these challenges, aiming to unlock the full potential of the European nuclear industry. Europe boasts competitive technology and industrial capacities, even on a global scale. European enterprises handle most components of the nuclear supply chain, although the global export market for large-scale nuclear power plants remains dominated by Russia. Looking to the future, the development of small modular and advanced modular reactors presents a promising opportunity for the European industry. However, domestic start-ups face intense competition from predominantly US enterprises, which appear to have secured earlier and more support from venture capitalists. In Europe, on the other hand, venture capital is scarcer and nuclear has traditionally been more dependent on public as opposed to private funding. The nuclear sector is a significant source of employment in Europe, supporting approximately 500,000 direct and indirect jobs, even in Member States without their own nuclear power plants. However, the age structure of the workforce presents a challenge. Over the next two decades, the sector will require up to 250,000 new recruits across a wide range of STEM professions, necessitating proactive strategies to attract and train the next generation.
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.
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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it