Bibliographic record
Abstract
T he oil crisis and fossil fuel price shocks in the 1970s boosted the prospects for energy efficiency, nuclear power and renewable forms of energy. Each of these alternatives experienced a surge of investment in R&D, demonstration projects and commercialization efforts. Each became the focus of government policy initiatives and public utility programs, sometimes attracting large subsidies. As the 1980s progressed, however, the prices of oil, natural gas and coal fell back to their historic levels. Unable to compete with fossil fuels except in special circumstances, each alternative experienced stagnating investment and declining policy interest. The emerging concern for sustainable energy in the 1990s, especially the focus on climate change among wealthier countries, produced a new window of opportunity for efficiency, nuclear and renewables, as advocates extolled their environmental virtues. Dramatic improvements in energy efficiency might eliminate the need for primary energy expansion, and even enable its contraction. Nuclear power produces clean electricity while emitting no local air pollutants, no regional acid emissions and no greenhouse gases. All renewables emit zero greenhouse gases and even biomass can be converted to electricity and hydrogen so that it too has zero local emissions. When the focus is a sustainable energy system, these are the “usual suspects.” Energy efficiency While energy efficiency is not a primary energy source, its potential contribution in the face of growing energy service needs was recognized three decades ago.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.007 |
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".