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Record W4210380471 · doi:10.1109/tmtt.2022.3142063

A Compact Wireless Passive Harmonic Sensor for Packaged Food Quality Monitoring

2022· article· en· W4210380471 on OpenAlexafffund
Robin Raju, Greg E. Bridges

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Supply Chain Traceability
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVaricapAntenna (radio)Wireless sensor networkElectronic engineeringSIGNAL (programming language)Electrical engineeringHarmonicEngineeringComputer scienceCapacitanceAcousticsPhysicsElectrodeComputer network

Abstract

fetched live from OpenAlex

There is currently a need to monitor food products while preserving quality and safety during long-term storage. In this article, a compact low-cost quasi-chipless sensor for monitoring the quality of high-value food items, such as milk and meat products, is presented. The sensor utilizes a dual-band dual-polarized annular ring antenna with an integrated harmonic generator and sensor to receive, modulate, and retransmit the interrogator signal. The resonant frequency of the receiving mode of the antenna is sensitized to the parameter being sensed using a varactor—pH electrode-based transduction scheme. The received signal is doubled using a diode frequency doubler circuit to minimize the clutter from the environment before retransmission. One application of the sensor for monitoring pH is presented. The sensor was shown to be able to successfully monitor the milk souring process.

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 score0.005

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 communication0.0000.001
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 head0.033
GPT teacher head0.271
Teacher spread0.238 · 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

Citations36
Published2022
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Microwave Theory and TechniquesSame topicFood Supply Chain TraceabilityFrench-language works237,207