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Record W2050727150 · doi:10.1049/el:20081445

Travelling-wave whispering gallery resonance sensor in millimetre-wave range

2008· article· en· W2050727150 on OpenAlexaff
Mohammad Neshat, Suren Gigoyan, D. Saeedkia, Safieddin Safavi‐Naeini

Bibliographic record

VenueElectronics Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWhispering-gallery waveWhispering galleryResonance (particle physics)DielectricMillimetre waveOpticsMillimeterMicrowaveExtremely high frequencyPerturbation (astronomy)Materials scienceSensitivity (control systems)OptoelectronicsPhysicsEngineeringElectronic engineeringResonatorAtomic physics

Abstract

fetched live from OpenAlex

A high sensitivity sensor with a simple structure is presented for analysis of (bio)chemicals in liquid or solution form. The proposed technique is based on the travelling-wave whispering gallery resonance perturbation method in the millimetre-wave range. The resonance modes are launched inside a dielectric disk through coupling into a dielectric image waveguide. The top surface of the disk is used as the sensing area where the resonance mode interacts with the sample. Theoretical analysis and experimental results for the proposed sensor are discussed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
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 studies0.0000.000
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 head0.016
GPT teacher head0.188
Teacher spread0.172 · 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.

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

Citations14
Published2008
Admission routes1
Has abstractyes

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