The Economic Future of Nuclear Power in Competitive Markets
Bibliographic record
Abstract
The question to be addressed is whether there is any economic future for nuclear power, especially in more competitive electricity markets and assuming the need for private capital. The answer to this question is yes and maybe. For operating plants, the economic gains can be high - some are money printing machines. Hence, there exists a strong interest in extending the life times of these reactors. For new plants, at least in more competitive electricity markets, the answer under present conditions is rather no unless major changes are made in the capital costs of these plants. This paper explores what the future might be if such changes can be made, what the most important changes are that need to occur, and how such changes might be brought about by a combination of changes in engineering and regulation. For one, a focus on cost-effective safety must be an essential part of the economics of future nuclear power plants. For another, full inclusion of waste disposal and decommissioning costs must be an integral part of nuclear cost analyses, as they generally are today, in order to minimize uncertainties concerning potentially open-ended liabilities. The question then is whether evolutionary improvements of current generation nuclear power plants can do the job or whether new nuclear technologies need to be developed and commercialized.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".