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Record W4214809649 · doi:10.1049/ell2.12448

Flex‐circuit resonant chip with Y5V multilayer capacitor for wireless temperature tracking

2022· article· en· W4214809649 on OpenAlexafffund
Ronish Patel, Madeshwaran Selvaraj, Kenichi Takahata

Bibliographic record

VenueElectronics Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsFLEXCapacitorChipMaterials scienceWirelessElectrical engineeringOptoelectronicsRLC circuitElectronic engineeringVoltageEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract This paper reports the first wireless thermometric device enabled using a surface‐mount capacitor microchip as the sensing element, offering a low‐cost, disposable, and flexible sensor potentially suitable for a wide range of application areas. The device is developed in the form of a resonant‐circuit chip, in which a Y5V‐type multilayer capacitor microchip that exhibits significant temperature dependence serves as a thermoresponsive element that varies the resonant frequency of the circuit upon a temperature change. The wireless sensor chips prototyped in conjunction with the flex‐circuit technology are tested to show their intended function with the frequency responses of up to 129 kHz/°C for ambient temperature variations. Wireless temperature tracking of a fluid‐flowing channel is experimentally demonstrated using the prototype.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.185
Teacher spread0.176 · 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
Published2022
Admission routes2
Has abstractyes

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