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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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 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 score0.085
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.033
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