MétaCan
Menu
Back to cohort
Record W2077045827 · doi:10.1109/aps.2013.6711706

Evaluating the efficiency of antennas used as sensors in microwave tissue imaging

2013· article· en· W2077045827 on OpenAlexaff
Kaveh Moussakhani, Reza K. Amineh, Natalia K. Nikolova

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicrowaveAntenna (radio)Microwave imagingDirectional antennaComputer scienceAcousticsPort (circuit theory)Electronic engineeringPhysicsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

A new method is proposed to evaluate the efficiency of antennas used in tissue microwave imaging. In this method, two identical antennas are employed, one transmitting and the other one receiving, in a setup where the scattering parameters are measured. Each antenna is considered as a two-port network and the antenna efficiency is expressed in terms of its equivalent network parameters. A signal flow graph (SFG) is developed for the two-port network formed by the two antennas and the medium between them. A system of equations is derived from the SFG and it is solved for the acquired data. This solution provides the efficiency of the antenna. The accuracy of the efficiency estimated from measured and simulated data is verified through comparison with full-wave simulations.

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 categoriesnone
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 score0.621
Threshold uncertainty score0.407

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 integrity0.0000.000
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 head0.017
GPT teacher head0.283
Teacher spread0.265 · 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.

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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicMicrowave Imaging and Scattering AnalysisFrench-language works237,207