SUSTAINABLE SUPPLY OF GLOBAL ENERGY NEEDS AND GREENHOUSE GAS REDUCTIONS
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 plants emit virtually no greenhouse gases over their full life-cycle. Consequently, continued operation of existing nuclear plants is recognized as essential to meeting even the modest greenhouse gas reduction targets of the Kyoto Accord. However, much expanded nuclear deployment will be needed as developing economies aggressively grow GDP with its associated growth in electrical power. Projecting to 2040 and based on the scenarios of the United Nations Intergovernmental Panel on Climate Change’s (IPCC), we have examined deploying increased non-carbon energy sources for electricity production, including further conversion of electricity to hydrogen using conventional low-temperaturc water electrolysis. Our NuWind© model has been used to calculate the production costs for hydrogen in typical potential markets, using the actual prices of electricity paid by the Alberta Power Pool and by the Ontario Grid. The analysis shows clearly that by optimizing the co-production of hydrogen and electricity (referred to as the H2/e process) the cost for hydrogen produced can comfortably meet the US Department of Energy’s target for realistic nuclear investment costs, hydrogen generation systems, and wind capacity factors. The synergy of nuclear plus wind power for hydrogen generation plus co-production of electricity improves the economics of harnessing wind energy to produce hydrogen.
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 | 0.001 |
| 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