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Record W7029070447

Impacto geopolítico del desarrollo de los hidrocarburos no convencionales

2014· article· en· W7029070447 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2014
Typearticle
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)BeneficiaryNatural gasFossil fuelBalance (ability)Medium termPetroleumSupply and demandMiddle East
DOInot available

Abstract

fetched live from OpenAlex

Non-conventional oil and gas resources are abundant and their production is economically viable. In addition, the geographical distribution of these resources\nhelps to diversify the traditional sources of supply currently highly concentrated in the Middle East and Russia. Stagnation and imminent fall in production of crude oil will make non-conventional oil to gain prominence in the future. Over the next decade, its increasing extraction, particularly in the United States and Canada, will help to temporarily weaken the hegemony of the OPEC which nevertheless will regain control of the market shortly after the mid-1920s. Meanwhile, the production of unconventional gas will extend in the future from North America to other parts of the world, consolidating\nits contribution to the global supply of gas on a long-term basis. The change in the geography of demand, whose centre is moving towards Asia, along with the changes introduced by the non-conventional hydrocarbons production in the current balance between exporting and importing countries,\nwill incur a reorganization of the trade flows of oil and natural gas, with implications upon the security of the global supply routes. The United States, which thanks to non-conventional, achieves the auto-sufficiency in the case of natural gas as well as a low degree of dependence on crude oil imports, is the big beneficiary in the medium term of the so-called non-conventional revolution. The European Union, by contrast, will see an increase on its imports\nand external dependence.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.227
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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