Near-Term Nuclear as the Nemesis of the Age of Pollution: Re-Engineering the Planet
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
The world’s carefree Age of Pollution is ending and energy technologies are scrambling for schemes that either capture their wastes or claim corresponding offsets with reductions elsewhere. Not before time. But the transition offers boundless opportunities for political and subsidies, fudges, and deceptions. Now is the time for nuclear fission, as the only technology already providing large-scale, pollution-free energy supplies, to claim proper recognition for its demonstrated pollution-free pedigree. Our industry knows that nuclear fission really is an intrinsically superior solution over those offered by the latter-day converts to sequestration and environmental cleanliness. Our singular strength is the availability of our technology. But we must inspire society with nuclear’s capacity to provide a comprehensive and affordable route to secure energy supplies with vigorous growth in its deployment, starting immediately. We must include hydrogen fuelling for vehicles to make our solution comprehensive. This paper outlines the economics. We could, however, so easily dissipate the advantage of nuclear’s availability. Programs to evolve advanced reactors should be a natural adjunct to a vigorous near-term program but it would be folly to compete for leadership in energy supply based on the promise of reactor designs that cannot be deployed until after 2020. What is needed is a transition strategy. Several countries with emerging economies are showing near-term leadership in commitment of new reactors but the developed world also needs much expanded deployment of nuclear. Without that, the transition to advanced designs after 2020 could be jeopardized.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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