International Energy Outlook 2016 With Projections to 2040
Bibliographic record
Abstract
The International Energy Outlook 2016 (IEO2016) presents an assessment by the U.S. Energy Information Administration (EIA) of the outlook for international energy markets through 2040. U.S. projections appearing in IEO2016 are consistent with those published in EIA’s Annual Energy Outlook 2015 (AEO2015). IEO2016 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, federal and state governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Department of Energy Organization Act of 1977 (Public Law 95-91), Section 205(c). The IEO2016 energy consumption projections are divided according to Organization for Economic Cooperation and Development members (OECD) and nonmembers (non-OECD). OECD members are divided into three basic country groupings: OECD Americas (United States, Canada, and Mexico/Chile), OECD Europe, and OECD Asia (Japan, South Korea, and Australia/New Zealand). Non-OECD countries are divided into five separate regional subgroups: non-OECD Europe and Eurasia (which includes Russia); non-OECD Asia (which includes China and India); Middle East; Africa; and non-OECD Americas (which includes Brazil). In some instances, the IEO2016 energy production models have different regional aggregations to reflect important production sources (for example, Middle East OPEC is a key region in the projections for liquids production). Complete regional definitions are listed in Appendix M. IEO2016 focuses exclusively on marketed energy. Nonmarketed energy sources, which continue to play an important role in some developing countries, are not included in the estimates. The IEO2016 projections are based on existing U.S. and foreign government laws and regulations. In general, IEO2016 reflects the effects of current policies—often stated through regulations—within the projections. EIA analysts attempt to interpret the likely effects of announced country targets when the implementation of those targets will require new policies that have not been formulated or announced.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.027 |
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".