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Record W2591140456 · doi:10.1109/lmwc.2017.2662321

High-Resolution RFID Liquid Sensing Using a Chipless Tag

2017· article· en· W2591140456 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.

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChipless RFIDQ factorResolution (logic)Radio frequencyElectronic engineeringHigh resolutionRadio-frequency identificationQuality (philosophy)EngineeringElectrical engineeringComputer sciencePhysicsResonatorRemote sensing

Abstract

fetched live from OpenAlex

A high-resolution radio frequency identification sensor using a chipless tag is reported. The proposed sensor is based on a passive resonant LC circuit tag with a regenerative loop in the reader, to compensate losses and increase the quality factor of the system. The high quality factor offers high-resolution readout with deep field penetration and thus enables distant, high-resolution sensing. The regenerative loop increases the tag quality factor at the reader from 135 to 20 000 in air. It also provides the flexibility of adjusting the quality factor by varying the applied dc voltage.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.044
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.020
GPT teacher head0.227
Teacher spread0.206 · 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