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Record W1544055581 · doi:10.1111/aspp.12118

South Korea's National Energy Plan Six Years On

2014· article· en· W1544055581 on OpenAlexaboutno aff
John S. Duffield

Bibliographic record

VenueAsian Politics & Policy · 2014
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
FundersKorea Energy Economics InstituteGeorgia State University
KeywordsRenewable energyPlan (archaeology)Quarter (Canadian coin)Nuclear powerFossil fuelGovernment (linguistics)Energy (signal processing)Energy policyAlternative energyNatural resource economicsEnvironmental protectionBusinessEconomic growthEnvironmental scienceGeographyEconomicsEngineeringWaste managementPhysics

Abstract

fetched live from OpenAlex

In 2008, South Korea adopted ambitious targets for reducing its dependence on energy imports and its carbon emissions simultaneously. The first National Energy Plan called for cutting energy intensity by nearly half and reducing the country's dependence on imported fossil fuels by more than one‐quarter by 2030. Fossil fuels would be replaced by nuclear power and renewable sources of energy, which together would meet nearly 40% of South Korea's energy needs. The achievement of these targets has been impeded by a number of obstacles, however. In response, the government has adjusted its goals, most recently with the adoption of a second national energy plan in January 2014. But especially in the critical area of nuclear power, the targets remain highly ambitious, and there are still reasons to question their feasibility. As a result, South Korea may have to moderate further its energy ambitions or redouble its efforts to achieve them.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.003

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 head0.207
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations12
Published2014
Admission routes1
Has abstractyes

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