It is time to re-think on environment, energy and economics (E3)
Bibliographic record
Abstract
The paper summarized some theories and facts related to Environment, Energy and Economics. This work paper provides some highlights about the theoretical issues and facts regarding to environmental pollutions and its effect on economy and the importance of relying on other source energy to fulfil the increasing demand of power or electricity. Moreover, the paper also discussed by making comparison between industrialized and developing countries about their effect on environment and their capacity in producing nuclear energy and production level and also the link between environmental science and economics. This paper concluded that the industrialized countries are not fulfilling their commitments. About 7 Billion Metric Tons of carbon equivalent harmful greenhouse gases are omitted by industrialized countries every year and the share of U.S.A is 24% followed by Japan & Developed European Nations which accounts 26%. Whereas developing nations contributes 13% other than china. Currently only eight countries are known to have a nuclear weapons capability and sixty further nuclear power reactors are under construction, equivalent to 17% of existing capacity, while over 150 are firmly planned, equivalent to 46% of present capacity. Sixteen countries depend on nuclear power for at least a quarter of their electricity. From developed countries, France is the first country that gets around three quarters of its power from nuclear energy. Whereas most developing countries under design and some of them have small share as compared to industrialized countries. After the disaster in Japan, many countries have changed policies on the implementation of nuclear power plants. In addition, the Italian Parliament was suspended for one year, the work of approving projects on the production of energy through nuclear power plants.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.011 | 0.027 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.024 |
| Insufficient payload (model declined to judge) | 0.016 | 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".