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Record W2080290614 · doi:10.1109/mias.2012.2221996

History of interior permanent magnet motors [History]

2012· article· en· W2080290614 on OpenAlexaff
M.A. Rahman

Bibliographic record

VenueIEEE Industry Applications Magazine · 2012
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEfficient energy useElectric motorEnergy consumptionAir conditioningAutomotive engineeringSynchronous motorPermanent magnet synchronous motorEngineeringBrushed DC electric motorMagnetComputer scienceMechanical engineeringElectrical engineeringAC motor

Abstract

fetched live from OpenAlex

Electric energy forms the backbone of modern civilization. Efficient energy consumption is the key to solving the 21st century global issues on climate change. Electric motors consume over 65% of the world's generated electrical power, and hence improvements in the efficiency of motors make significant imprints on reduction of its consumption. A close examination reveals that different technological advancements and market forces have combined sometimes in fortuitous ways to accelerate the development of high-efficiency interior permanent magnet (IPM) synchronous motors. The objective of this article is to provide a short introduction to the recent emergence of high-efficiency and high-performance IPM synchronous motors for applications such as in automobiles and air conditioners to reduce global warming and save energy.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.012

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 head0.020
GPT teacher head0.219
Teacher spread0.199 · 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
GenreEmpirical

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

Citations69
Published2012
Admission routes1
Has abstractyes

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