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Record W4366204747 · doi:10.1109/tpel.2023.3263351

Editorial: Special Section on Patent-Related Short Articles

2023· editorial· en· W4366204747 on OpenAlexaff
Yunwei Li, Vivek Agarwal, Xiongfei Wang

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2023
Typeeditorial
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSpecial sectionSection (typography)VisibilityElectronicsEngineeringPower electronicsTelecommunicationsComputer scienceElectrical engineeringEngineering physicsGeography

Abstract

fetched live from OpenAlex

This papers in this special section focuses on a collection of short articles describing new ideas and concepts in the areas of power electronics that have been patented in recent years. The letters from this special section aim to improve the visibility of recently patented ideas to a wide range of audiences. It can also highlight the new development since the patent filing, idea adoption in practice, and the impact of power electronics development on the industry and society.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.023
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0070.004
Open science0.0030.001
Research integrity0.0130.014
Insufficient payload (model declined to judge)0.0230.023

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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