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Record W2493029458 · doi:10.1049/iet-smt.2016.0221

Mutual inductance and magnetic force calculations for coaxial bitter disk coils (Pancakes)

2016· article· en· W2493029458 on OpenAlexaff
Slobodan Babić, Cevdet Akyel

Bibliographic record

VenueIET Science Measurement & Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsInductanceCoaxialElectrical engineeringMaterials sciencePhysicsNuclear magnetic resonanceAcousticsEngineeringVoltage

Abstract

fetched live from OpenAlex

Recently Y. Ren and J.T. Conway calculated the mutual inductance and the magnetic force between an ordinary coil and a bitter coil or between two bitter coils. The bitter coil is the coil with inverse radial current density. In this study, the authors calculate the mutual inductance and the magnetic force between two disk coils (pancakes) with inverse radial current density. This coil configuration with proposed current density seems to be similar to bitter coils. Both calculations give the semi‐analytical expressions either for mutual inductance or for the magnetic force. Also they derived the self‐inductance for the disk coil with radial current density which is obtained in closed form. The results of this method are compared by those obtained by the modified filament method for the presented configuration.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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