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Record W4409326439 · doi:10.1109/jsen.2025.3557969

One-Port and High-Sensitivity Angular Displacement Sensor Based on a Microwave Quarter-Wavelength Resonator

2025· article· en· W4409326439 on OpenAlexaboutno aff
Víctor-Manuel Cante-Saloma, José‐Luis Olvera‐Cervantes, M. Tecpoyotl‐Torres, Alonso Corona‐Chávez

Bibliographic record

VenueIEEE Sensors Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsResonatorMicrowavePort (circuit theory)Sensitivity (control systems)OptoelectronicsWavelengthMaterials scienceOpticsDisplacement (psychology)Electrical engineeringQuarter (Canadian coin)PhysicsEngineeringElectronic engineeringTelecommunications

Abstract

fetched live from OpenAlex

This work presents a high-sensitivity angular displacement sensor using microstrip technology. The sensor configuration includes a stator that incorporates a quarter-wavelength angular segment, which is short-circuited through a via hole. The rotor is designed as a transmission line, precisely aligning with the stator’s angular segment to ensure optimal interaction. This paper provides a comprehensive description of the design methodology and presents the equivalent electrical circuit. Additionally, detailed simulation and measurement results are included. To ensure accuracy, the sensor underwent multiple measurements, which were statistically analyzed. The sensor achieves a dynamic range of 160°, exhibiting excellent linearity across this range and a high sensitivity of 4.7 MHz/°. It also demonstrates a resolution of 2° and maintains precision for each indicated angle, with an average standard deviation of 2.243 × 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> GHz. Due to its single-port design, this sensor is particularly well-suited for seamless integration as a sensor node within Wireless Sensor Networks (WSN).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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.

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

Citations4
Published2025
Admission routes1
Has abstractyes

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