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Record W4235454321 · doi:10.1002/9781119453550.ch12

Conclusion

2019· other· en· W4235454321 on OpenAlexaff
Hassan Farhangi, G. Joós

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsMcGill UniversityBritish Columbia Institute of Technology
Fundersnot available
KeywordsMicrogridSmart gridRenewable energyReliability (semiconductor)Computer scienceControl (management)Systems engineeringRisk analysis (engineering)TelecommunicationsEngineeringPower (physics)BusinessElectrical engineering

Abstract

fetched live from OpenAlex

This chapter describes challenges and methodologies for each research topic within each of the three themes: operation, control, and protection of smart microgrids; smart microgrid planning, optimization, and regulatory issues; and smart microgrid communication and information technologies. Protection strategies and the required implementation technologies for remote microgrids may necessitate special consideration in terms of control and operational strategies of the renewable resources. Microgrids are often touted as a technology that can improve local system reliability, aid in the integration of renewable energy resources, and lead to enhanced power quality. The communications infrastructure that serves smart microgrids needs to be deployed as a hierarchy of networks, each of which may be realized using various wired and wireless technologies. A robust and reliable sensor network is needed to provide information on overall grid integrity. The microgrid communication infrastructure and integrated data-management system are expected to facilitate the transfer of this information to central supervisory control.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.747
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2530.136

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 head0.003
GPT teacher head0.176
Teacher spread0.173 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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