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Record W1972668369 · doi:10.1063/1.4747915

On physical aspects of the Jiles-Atherton hysteresis models

2012· article· en· W1972668369 on OpenAlexafffund
Sergey E. Zirka, Yuriy I. Moroz, Robert G. Harrison, Krzysztof Chwastek

Bibliographic record

VenueJournal of Applied Physics · 2012
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHysteresisPhenomenology (philosophy)Energy balanceStatistical physicsBalance (ability)Phenomenological modelPhysicsMechanicsMathematicsThermodynamicsCondensed matter physicsPsychology

Abstract

fetched live from OpenAlex

The physical assumptions underlying the static and dynamic Jiles-Atherton (JA) hysteresis models are critically analyzed. It is shown that the energy-balance method used in deriving these models is actually closer to a balance of coenergies, thereby depriving the resulting JA phenomenology of physical meaning. The non-physical basis of its dynamic extension is demonstrated by a sharp contrast between hysteresis loops predicted by the model and those measured for grain-oriented steel under conditions of controlled sinusoidal flux density at frequencies of 50, 100, and 200 Hz.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.025
GPT teacher head0.237
Teacher spread0.211 · 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 designTheoretical or conceptual
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

Citations143
Published2012
Admission routes2
Has abstractyes

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