Technology Intelligence: Transformative Trends and Technological Synergies for the Smart Grid
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.020 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".