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Record W4402293772 · doi:10.1002/9781119909880.ch5

Technology Intelligence: Transformative Trends and Technological Synergies for the Smart Grid

2024· other· en· W4402293772 on OpenAlexaboutno aff
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Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningGridData scienceEngineeringComputer scienceSociologyGeography

Abstract

fetched live from OpenAlex

The smart grid, a pivotal component in the realm of sustainable energy management, is a transformative technology with multifaceted characteristics that redefine contemporary scientific discussions. This study delves into the intricacies of smart grid technology, emphasizing its significance in fostering communication, enhancing energy efficiency, and fortifying reliability. The ascendancy of smart grids has spurred a paradigm shift in technology and engineering management, necessitating collaboration between engineers and technologists. Technology management strategies focus on optimizing and updating advanced smart grid features, while engineering management oversees the physical design and operation of energy infrastructure. This collaboration, witnessed in the collaboration of technology and engineering management, becomes paramount for the successful development and implementation of smart grids. In conjunction with the qualitative exploration, a comprehensive dataset covering records from 1991 to 2023, consisting of 20 897 records, provides valuable insights. This dataset, rich in various document types, reflects scholarly contributions and research outputs across different domains, contributing to a robust knowledge base. A visual analysis of major thematic clusters within a network unveils significant research areas and their temporal contexts. Keywords related to smart grid technology, evaluated using Social Network Analysis indicators, illuminate critical research areas from basic technological concepts to operational and management strategies. The study extends its analysis to author productivity and global contributions. High-profile researchers contribute significantly to smart grid technology, exemplifying the field's growth and influence. The h-index, indicating academic impact, underscores the leadership of countries such as the United States, China, Canada, the United Kingdom, and Australia in smart grid technology research. In conclusion, this study offers a comprehensive understanding of smart grid technology, encompassing its characteristics, thematic clusters, author contributions, and global research landscape. This holistic exploration contributes to the ongoing discourse surrounding sustainable energy management and lays the groundwork for future advancements in the field.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.273
Threshold uncertainty score0.515

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.236
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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