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Record W2598109358 · doi:10.1504/ijgei.1991.063683

Is it possible and expedient to create a global energy network

2014· article· en· W2598109358 on OpenAlexaboutno aff
Yuri N. Rudenko, Victor V. Yershevich

Bibliographic record

VenueInternational Journal of Global Energy Issues · 2014
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsnot available
Fundersnot available
KeywordsElectric power transmissionElectricityPower transmissionElectric powerElectric power systemSubmarineTransmission (telecommunications)ChinaTransmission systemPower (physics)Electrical engineeringTelecommunicationsEngineeringGeographyMarine engineering

Abstract

fetched live from OpenAlex

The world–wide distribution of primary energy resources does not correspond to the geographical allocation of zones of their consumption. Electricity production and power–plant generating capacity grow everywhere including regions where there are no resources. Electrical power systems already cover not only individual countries, but also groups of countries, and even entire regions. Therefore, the following problem arises: is it possible and expedient to interconnect regional power systems so as to form a global energy network? The technical facilities for such a network are already available: DC transmission systems with voltages up to ± 750 kV and AC transmission systems with voltage up to 1200 kV. The transfer capacities of such transmission systems can reach 5000–6000 MW. There are no technical limitations on constructing international DC electrical transmission systems through any straits. The longest existing DC submarine cable link from Finland to Sweden along the bottom of Botnic Bay has a voltage of 400 kV and a cable length of about 200 km. The efficiency of large regional and international electrical power system interconnections between East Europe–West Europe, USSR–Canada–USA, USSR–Japan, USSR–China is to be investigated. The five countries participating in these interconnections (USA, USSR, Japan, China, Canada) generate almost 60 per cent of all the electric power produced in the world.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.010
Open science0.0010.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0140.005

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 head0.008
GPT teacher head0.271
Teacher spread0.263 · 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 designTheoretical or conceptual
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

Citations9
Published2014
Admission routes1
Has abstractyes

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