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Record W2044393823 · doi:10.1063/1.373164

Modeling the magnetoimpedance in anisotropic wires

2000· article· en· W2044393823 on OpenAlexafffund
David Ménard, L. G. C. Melo, Mohammed Réda Britel, P. Ciureanu, A. Yelon, M. Rouabhi, R. W. Cochrane

Bibliographic record

VenueJournal of Applied Physics · 2000
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsUniversité de MontréalPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGiant magnetoimpedanceAnisotropyCondensed matter physicsMaterials scienceMagnetic fieldField (mathematics)Amorphous solidLow frequencyMagnetic anisotropyRange (aeronautics)Nuclear magnetic resonanceGiant magnetoresistanceMagnetoresistancePhysicsComposite materialMagnetizationOpticsChemistry

Abstract

fetched live from OpenAlex

We have developed a theory of giant magnetoimpedance (GMI) in ideal anisotropic magnetic wires, which is valid over a broad field and frequency range. The emphasis is put on the moderate frequency GMI response in the low field region, where the wire is not saturated. The model agrees with experimental data on amorphous CoFeSiB wires, over broad frequency and field ranges, but does not correspond to an experiment at low field.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.199
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations20
Published2000
Admission routes2
Has abstractyes

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