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Record W2105113713 · doi:10.1109/tmag.2008.2001663

Demagnetizing Factors for Nonuniform Nonlinear Cylinders and Rectangular Prisms

2008· article· en· W2105113713 on OpenAlexaff
A.V. Farahani, A. Konrad

Bibliographic record

VenueIEEE Transactions on Magnetics · 2008
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMagnetizationDemagnetizing fieldNonlinear systemMagnetic fieldCondensed matter physicsMagnetic energyPosition (finance)Magnetic susceptibilityPhysicsEnergy (signal processing)MagnetostaticsMechanics

Abstract

fetched live from OpenAlex

Current methods to obtain fluxmetric and magnetometric demagnetizing factors assume a uniform susceptibility and solve initially the surface magnetic pole density. In this paper, a different approach is applied. This approach considers susceptibility as a function of position and finds the field distributions directly. It is proved that the magnetization distribution and the corresponding magnetic field minimize the magnetostatic energy and thus are the unique solution to the given magnetostatic problem. To verify the method, both rectangular and cylindrical magnetic media with nonlinear magnetization curves or a step change in susceptibility are considered.

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: none
Teacher disagreement score0.002
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.235
Teacher spread0.203 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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