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Record W2063723080 · doi:10.1002/pssb.200642613

Effects of anisotropic exchange on the micromagnetic domain structures

2007· article· en· W2063723080 on OpenAlexaff
D. M. Schaadt, Roman Engel‐Herbert, T. Hesjedal

Bibliographic record

Venuephysica status solidi (b) · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnisotropyCondensed matter physicsMicromagneticsIsotropyDomain (mathematical analysis)Exchange biasPhysicsDomain wall (magnetism)MagnetizationTensor (intrinsic definition)Exchange interactionRelaxation (psychology)Phenomenological modelMagnetic domainMagnetic anisotropyMaterials scienceGeometryMathematicsMagnetic fieldMathematical analysisFerromagnetismOpticsQuantum mechanicsPsychology

Abstract

fetched live from OpenAlex

Abstract We have investigated the influence of anisotropic exchange on the micromagnetic domain structure. Three‐dimensional simulations based on the Landau–Lifshitz–Gilbert equation were performed incorporating a generalized tensor representation of the exchange following a phenomenological approach. In comparison to isotropic exchange, which is usually used in micromagnetic simulations, anisotropic exchange significantly affected the equilibrium distribution of the magnetization. The formation of slanted domain walls aligning in the direction of stiffest exchange and the deformation of edge domains were the most prominent consequences. In general, we found that anisotropic exchange may have profound effects on magnetic nanostructures. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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