MétaCan
Menu
Back to cohort
Record W1978866396 · doi:10.1002/jnm.773

Torque calculation between circular coils with inclined axes in air

2010· article· en· W1978866396 on OpenAlexafffund
Slobodan Babić, Cevdet Akyel

Bibliographic record

VenueInternational Journal of Numerical Modelling Electronic Networks Devices and Fields · 2010
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTorqueElectromagnetic coilInductanceCross section (physics)AcousticsPhysicsMechanicsSection (typography)EngineeringElectrical engineeringComputer scienceVoltage

Abstract

fetched live from OpenAlex

Abstract In this paper we derive new semi‐analytical expressions for calculating the electromagnetic torque between inclined circular coils in air. The torque calculation has been obtained from the corresponding mutual inductance between inclined circular coils using the filament method. The coils of rectangular cross‐section whose centers are at the same and the different axes have been considered. From this general case it is possible to calculate the torque between all possible coil combinations either with rectangular or neglected cross‐section. Results obtained by the presented approach are in very good agreement with already published data. This method can be used for industrial electromagnetic devices such as torque sensors, transducers and torque‐measuring devices. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.245
Teacher spread0.233 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Numerical Modelling Electronic Networks Devices and FieldsSame topicSensor Technology and Measurement SystemsFrench-language works237,207