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Record W4307532257 · doi:10.1002/mmce.23528

A compact radio frequency identification tag antenna with loaded coupling rings for <scp>two‐side anti‐metal</scp> design

2022· article· en· W4307532257 on OpenAlexaff
Chenchen Niu, Jiade Yuan, Zhizhang Chen, Zhimeng Xu

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsDalhousie University
FundersScience and Technology Planning Project of FuzhouNational Natural Science Foundation of China
KeywordsAntenna (radio)Sensitivity (control systems)Coupling (piping)PlanarRadio frequencyTransmission (telecommunications)Materials sciencePhysicsTelecommunicationsOptoelectronicsElectrical engineeringElectronic engineeringComputer scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

A compact ultra-high frequency radio frequency identification tag antenna loaded with a pair of rectangular coupling rings for two-side anti-metal performance is proposed. It evolves from a planar inverted-F antenna and has the same upper and lower structures. A pair of coupling rings is symmetrically loaded on the inner sides of the upper and lower substrates, and the tag's maximum power transmission coefficient can be achieved when either side of the antenna is placed on a metallic plate. The proposed tag antenna maintains a compact size of 34 mm × 28 mm × 5 mm. The measured results show that it has the lowest sensitivity of −14.8 dBm when the lower side is on a metallic plate and the lowest sensitivity of −14.2 dBm when the upper side is on a metallic plate. The proposed tag antenna is featured in a compact size, low sensitivities, and anti-metal performance on two sides. It may be used in the areas such as the industrial internet of things.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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