A comparative study on energy review among the developed and emerging nations
Bibliographic record
Abstract
The study explored the comparison of energy scenario and CO 2 emission among the developed and emerging nations such as USA, Canada, China, Brazil and India. It is recognized that the world is under serious threat of global warming, thus immediate actions are required to combat against it globally. The objective of this study was to examine the current situation of energy and emission in this high energy consumes countries. Total global coal production has been increased up to 35.36% in 2010 compare to 2001, and 5.5% increased compare to 2009. The production of natural gas has been increased in a similar manner. China alone contribute 26% of the world total CO 2 , USA 18%, India 5%, Canada and Brazil 2% in 2009 due to the high consumption of coal, natural gas and petroleum. But the per capita emission of CO 2 was very high in developed countries such as USA’s per capita emission was more than 3, 13 and 7 times than China, India and Brazil in 2009. So it is very important to adopt low e-technology and energy efficient initiatives in the energy and emission driving countries.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".