A GEOGRAFIA DO PETRÓLEO EM TRANSIÇÃO: CONSIDERAÇÕES A PARTIR DAS DESCOBERTAS DE FONTES NÃO CONVENCIONAIS DE PETRÓLEO NA AMÉRICA
Bibliographic record
Abstract
DOI: http://dx.doi.org/10.12957/geouerj.2014.12864 This article presents some comments regarding the novel geopolitics of oil due to the recent discovery of huge oil deposits of unconventional sources in regions outside of the shaft Middle East-North Africa, specifically in the U.S. shale, tar sands in Canada and pre-salt in Brazil. This study aims outlining some possible geopolitical scenarios taking into consideration the ingress of these new sources of oil in the world trade. In order to do so, this article is organized into three parts.Initially a brief assessment on the state of the art of current studies on the geopolitics of oil in Brazil will be presented. Then, will be exposed the geographical distribution of the oil industry in the world, the main proven reserves, the most important producing and consuming countries and regions, and major refining activities, with emphasis on the role of large companies. Finally, the possibilities of geographical restructuring and geopolitical reordering of oil in the world are presented, considering these new unconventional energy sources in the US, Canada and Brazil.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".