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Record W2010633859 · doi:10.1063/1.2728776

Second harmonic of nonlinear magnetoimpedance in amorphous magnetic wires with helical anisotropy

2007· article· en· W2010633859 on OpenAlexaff
D. Seddaoui, David Ménard, P. Ciureanu, A. Yelon

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsPolytechnique MontréalRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsAmplitudeCondensed matter physicsAnisotropyAmorphous solidMagnetic fieldField (mathematics)HarmonicQuasistatic processIntensity (physics)Giant magnetoimpedanceMaterials scienceLow frequencyNuclear magnetic resonancePhysicsChemistryOpticsMagnetoresistanceGiant magnetoresistance

Abstract

fetched live from OpenAlex

The axial magnetic field dependence of the second harmonic of giant magnetoimpedance in Co-rich amorphous wires with helical anisotropy has been measured to high field resolution in the current amplitude range of 2–14 mArms and frequency range of 200 kHz–3 MHz. We have found that the intensity of the inner peaks of the four-peak structure increases with current amplitude until a threshold value, and then begins to decrease without changing position, whereas the outer peaks decrease monotonically and move to higher field. When frequency is increased from 200 kHz to about 2 MHz, all of the four peaks increase in height and move to higher field. Beyond 2 MHz, all of the peaks move to lower field; the intensity of the inner peaks decreases while the outer peaks continue to increase. At low frequency and current, a third pair of peaks appears between the two inner peaks and disappears when the frequency increases. Using a simple quasistatic model, the four-peak and six-peak structures are explained qualitatively. The variation with the current amplitude is also understood. However, accurate determination of the second harmonic signal and its frequency dependence requires a more complete model.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.586

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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 designBench or experimental
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

Citations14
Published2007
Admission routes1
Has abstractyes

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