MétaCan
Menu
Back to cohort
Record W2963794332 · doi:10.1109/access.2019.2930956

A Highly Miniaturized and Inherently Conjugately Matched Folded Dipole-Based RFID Tag Antenna

2019· article· en· W2963794332 on OpenAlexafffund
Sanghamitro Das, Hossein Saghlatoon, Pedram Mousavi, Ashwin K. Iyer

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesCMC Microsystems
KeywordsDipole antennaAntenna (radio)DipoleImpedance matchingLoop antennaElectrical impedanceAntenna measurementComputer scienceRadiation patternAntenna efficiencyOptoelectronicsCoaxial antennaMaterials sciencePhysicsElectronic engineeringElectrical engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A novel miniaturized printed folded dipole antenna has been designed and its usefulness as an RFID tag has been demonstrated. It has been shown that the input impedance of the antenna can be engineered to achieve the required complex impedance by employing series-LC loading and unequal arm widths. The end result is a conjugately well-matched 75%-miniaturized folded dipole antenna that does not require an external matching network and exhibits a useful 30.93% radiation efficiency and 8.09 m simulated read range. Experimental validation of a fabricated prototype demonstrates excellent agreement with simulations.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.249
Teacher spread0.236 · 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

Citations18
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueIEEE AccessSame topicRFID technology advancementsFrench-language works237,207