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Record W4234431429 · doi:10.1109/mpel.2020.3047328

CFP for PEDG 2021

2021· article· en· W4234431429 on OpenAlexaff
Jinjun Liu, Željko Jakopović, Sudip K. Mazumder, Juan Carlos Balda, Frede Blaabjerg, Liuchen Chang, Rik Dedoncker, Deepak Divan, J.H.R. Enslin, Gerard Hurley, Fred C. Lee, L H Lorenz, Cruz Denizar, Martin Ordonez, Dong Tan, Mark Xu, Suman Debnath, Jianzhe Liu, Ankit Gupta, Lina He

Bibliographic record

VenueIEEE Power Electronics Magazine · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of British ColumbiaUniversity of New Brunswick
Fundersnot available
KeywordsVirologyComputer scienceBusinessMedicine

Abstract

fetched live from OpenAlex

GenerationSystems (PEDG 2021) will be held between June 28 -July 1, 2021.This international symposium, sponsored by IEEE Power Electronics Society (PELS) and organized by the PELS Technical Committee on Sustainable Energy Systems, will provide a venue for experts to present the results of their cutting-edge research in power electronics and distributed generation (DG) systems.PEDG 2021 will feature all-virtual plenary speeches, tutorials, and regular technical and poster sessions on theory, analysis, design and development, testing, deployment, and impact of power electronics for DG and systems, energy storage systems, and sustainable sources.All papers presented at PEDG 2021 will appear on IEEE Xplore.Three papers will be awarded "Best Paper", as selected from the paper submissions.PEDG 2021 will be hosted entirely on an engaging and easily accessible online platform.Attendees will gain a unique opportunity to connect with the global power electronics community and gain access to the various technical sessions that PEDG 2021 has to offer.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.222
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.7780.650

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 head0.055
GPT teacher head0.417
Teacher spread0.362 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2021
Admission routes1
Has abstractyes

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