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Renewable Energy Resources Potentials in G8 and BRICS

2021· article· en· W3200376349 on OpenAlexaboutno aff
Luo Ji, Shuo Li, Jingtao Li, Li‐Ting Liu, Ming-hui Wang

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyNatural resource economicsHydropowerEnvironmental impact of the energy industryFeed-in tariffEnergy subsidiesEnergy developmentChinaBusinessRenewable energy creditEnergy engineeringEnergy policyFossil fuelWind powerSustainable developmentEnvironmental protectionEconomicsEnvironmental scienceGeographyEngineeringEcologyWaste management

Abstract

fetched live from OpenAlex

Abstract Renewable energy is emphasized globally due to its potential to contribute to economy and energy sustainable development, as well as mitigate the climate change. Developed and developing countries have set their sights on renewable energy as increasing exhaustion of the fossil energy and deterioration of environmental problem. This article focuses on concise summary and statistic of renewable energy resources potentials, including solar energy, wind energy, bioenergy, geothermal energy, and hydropower. Meanwhile, it provides the renewable energy development status of G8(US, UK, France, Germany, Italy, Canada, Japan, Russia) and BRICS (Brazil, Russia, India, China, and South Africa) countries. The result indicates that renewable energy resources are abundant, especially in China, the US and Russia. Each country has its own resources advantage. China has abundant renewable energy resources but still needs to accelerate renewable energy technology innovation. At last, suggestions are proposed for policy makers on renewable energy penetration.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.991

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.194
Teacher spread0.184 · 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 designBench or experimental
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

Citations3
Published2021
Admission routes1
Has abstractyes

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