Study on Current Status and Future Developments in Nuclear-Power Industry of the World
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
Currently, nuclear power plays a quite visible role in the world electricity generation (∼11%). However, before the Fukushima Nuclear Power Plant (NPP) severe accident in March of 2011, NPPs generated about 14% of the world’s electricity. Accounting that after, mainly, Chernobyl NPP severe accident a number of power reactors built and put into operation in the world decreased from 120 within 1985–1990 to about 22 per 5 years (within 1995–2015), we might face a significant shortage of operating power reactors within 2030–2040. Therefore, it is important to evaluate current status of nuclear-power industry and to make projections on near (5–10 years) and far away (10–25 years and beyond) future trends in nuclear-power industry. In the current paper statistics on all current nuclear-power reactors were analyzed and based on that future trends were estimated in terms of types of reactors to be left after 10 years, new types of reactors to be put into operation, projections of how many reactors and of which types will be build. To make any projections an average operating term of power reactors should be estimated. In the current paper a nuclear-power-reactor operating term of 45 years was considered. Also, rates of building and putting into operation power reactors worldwide were estimated, and several scenarios of future developments in nuclear-power industry in the world and in selected countries were considered.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it