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Record W4385731863 · doi:10.1109/access.2023.3304245

Near-Field Reception of Dipole Sources Using a Dual-Loaded Loop

2023· article· en· W4385731863 on OpenAlexaff
Christopher G. Hynes, Rodney G. Vaughan

Bibliographic record

VenueIEEE Access · 2023
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMagnetic dipoleDipoleLoop (graph theory)Loop antennaElectric fieldPhysicsDual loopDipole antennaAntenna (radio)Magnetic fieldElectric dipole momentField (mathematics)Port (circuit theory)Electromagnetic fieldComputational physicsComputer scienceQuantum electrodynamicsElectrical engineeringTelecommunicationsMathematicsEngineeringQuantum mechanics

Abstract

fetched live from OpenAlex

The dual-loaded loop is a two-port antenna configured as two half-loops. Its advantage is the ability to sense two field components instead of the single component of a single-port loop. In this study, the theory of the dual-loaded loop is extended to cases for sensing arbitrarily located electric and magnetic dipole sources. New general expressions are presented for the tangential electric field on a loop resulting from electric and magnetic dipole sources in the near-field of the loop. From these field expressions, closed-form approximations for the current at the ports are obtained. The approximations are shown to be very accurate through simulation, but can degrade when the separation distance between the dipole source and loop is small. The worst discrepancy occurs when an electric dipole is close to and aligned with one of the ports. These expressions provide a benchmark for checking numerical and physical results for this class of sensor.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.061
GPT teacher head0.300
Teacher spread0.239 · 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 designBench or experimental
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

Citations2
Published2023
Admission routes1
Has abstractyes

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Same venueIEEE AccessSame topicElectromagnetic Compatibility and MeasurementsFrench-language works237,207