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Record W4214920246 · doi:10.1109/mpe.2021.3134149

Integration of Small Modular Reactors Into Renewable Energy-Based Standalone Microgrids: An Energy Management Perspective

2022· article· en· W4214920246 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Power and Energy Magazine · 2022
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsRenewable energyGreenhouse gasEnvironmental economicsEnvironmental scienceWind powerDiesel fuelElectricity generationElectricityBusinessEngineeringWaste managementPower (physics)Economics

Abstract

fetched live from OpenAlex

The environmental impact of human activities has become a significant consideration when making energy infrastructure decisions. To reduce energy poverty worldwide, there is growing interest in providing electricity in an environmentally sustainable way that minimizes greenhouse gas emissions. The same applies to the energy supply for off-grid industrial activities, such as mining projects and remote communities. These applications have traditionally been served by diesel generators, and more recently by wind-diesel hybrid power systems. Diesel and fuel oils are notorious for the high cost of transportation to remote sites, and for emissions of particulate pollution and greenhouse gasses. Such emissions can profoundly impact the environment in comparison to other types of power generation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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