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Record W4255726569 · doi:10.1109/tmag.2020.3042580

IEEE Magnetics Society Information

2020· article· en· W4255726569 on OpenAlexaff
Masahiro Yamaguchi, Atsufumi Hirohata, Manuel Ázquez, Peter Lau, Larissa Fischer, Simon Panina, Teruo Greaves, Mathias Ono, Thomas Kl Äui, Elke Arenholz, Katsuji Nakagawa, David Jiles, Johannes Paulides, Olga Kazakova, G. Reiß, Nicoleta Lupu, Shinji Yuasa, Hendrik Jean, Anne Incorvia, Lucian Prejbeanu, G. V. Kurlyandskaya, Montserrat Rivas, K. Nakamura, Yukiko Takahashi, J. Faßbender, Distinguished Lecturers, Bethanie Stadler Conference, Rudolf Sch, Äfer Education, Brian Finance, Mark Membership, Hans Nominations, Yamaguchi Bylaws, Ron Publications, Philip Publicity, Oksana Chapters, Mingzhong Wu, Dario Albertini, Elke Arena, Davide Arenholz, Jen-Yuan Bossini, Gardner Kannan Krishnan, Cristina Ómez-Polo, L. H. Lewis, Shikha Jain, Mark Kief, Markus Ünzenberg, Mathias Kl, Äui Cajetan, Ikenna C. Nlebedim, Philip W. T. Pong, Dan Wei, R.V. Ramanujan, John Q. Xiao, Jordi Sort, V Ñas, Sachiko Yamaguchi‐Sekino, Anjan Soumyanarayanan, Jinbo Yang, Plamen Stamenov, Wei Zhang, Nian X. Sun, Barry Zink, Ron Goldfarb, Petru Andrei, R. H. Victora, Toshio Fukuda, Susan Kathy, Land, Kathleen Kramer, Joseph Lillie, Márcio das Chagas Moura, Stephen Phillips, Keka Sarkar, Kukjin Chun, Robert Fish, James W. Conrad, John Verboncoeur, Stephen Welby, Thomas Siegert, Business Administration, Julie Cozin, Corporate Governance, Donna Hourican, Jamie Moesch, Sophia Muirhead, Chris Brantley, Ieee-Usa Cherif, Karen Hawkins, Cecelia Jankowski, Geographic Activities, Steven Heffner

Bibliographic record

VenueIEEE Transactions on Magnetics · 2020
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.184
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractno

Explore more

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