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Record W3212236747 · doi:10.3389/fenrg.2021.735551

Energy Efficiency and Pollution Control Through ICTs for Sustainable Development

2021· article· en· W3212236747 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Energy Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsSustainable developmentEnvironmental pollutionGovernment (linguistics)Efficient energy useEnvironmental economicsControl (management)Block (permutation group theory)BusinessPollutionDeveloping countryEnvironmental protectionComputer scienceEnvironmental scienceEconomic growthEngineeringPolitical scienceEcologyEconomicsMathematics

Abstract

fetched live from OpenAlex

The goal of this paper is to prove the necessity for a more thorough consideration and more active use of the modern ICTs for the technological support for the practical implementation of the SDGs’ ecological block in the aspect of the increase of energy efficiency and environmental pollution control. The originality of this paper is as follows: it develops a proprietary methodology of evaluating the technical readiness (level of the development of ICTs) for implementing the ecological block of the SDGs, which envisage the increase of energy efficiency and the growth of environmental pollution control. The highest (but moderate) technological readiness to implement the ecological block of the SDGs among developed countries has been shown by Canada (14.42 points) and Denmark (11.03 points), among developing countries—China (7.72 points). As a result, it has been proved that UCTs are a perspective tool of the practical implementation of the ecological block of the SDGs, stimulating the increase of energy efficiency and improving the environment pollution control. For developed countries, it is recommended to increase the use of Big data and AI analytics by 90.36% and increase the use of ICTs in E-government by 89.74%. This will allow achieving the growth of energy efficiency by 8.28% and the decrease of environmental pollution by 28.41%. In developing countries, it is recommended to increase world robots distribution by 14.17% and increase the use of ICTs in E-government by 76.74%. This will allow increasing the energy efficiency by 16.77% and decreasing the level of environmental pollution by 15.54%. This paper’s contribution to literature (innovative aspect of research) consists in filling the gap of the uncertainty (underdevelopment) of the tools for practical implementation of the SDGs ecological block. This paper has demonstrated the substantial potential of ICTs in the stimulation of the growth of energy efficiency and reduction of environmental pollution in developed and developing countries.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.029
GPT teacher head0.247
Teacher spread0.218 · 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