MétaCan
Menu
Back to cohort
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 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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
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 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of RF and Microwave Computer-Aided EngineeringSame topicAntenna Design and AnalysisFrench-language works237,207