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Tasks of Improving Medical Antennas for Microwave Radiothermometry of Biological Objects (review)

2022· article· en· W4307166304 on OpenAlex
V. Yu. Leushin, S. V. Agasieva, Sergey Vesnin, M. K. Sedankin, I. O. Porokhov, Nataliya Vetrova, Е. Н. Горлачева, M. Sidorova

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

VenueInfocommunications and Radio Technologies · 2022
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsHyperion Technologies (Canada)
Fundersnot available
KeywordsConformal antennaMicrowaveDirectional antennaAntenna (radio)Computer scienceReconfigurable antennaMicrowave transmissionElectronic engineeringConformal mapMicrowave imagingSlot antennaEngineeringMicrostrip antennaTelecommunicationsMathematicsAntenna efficiency

Abstract

fetched live from OpenAlex

An overview of the state of antennas development of various types used in medical microwave radiothermographs is given. The problems of modern microwave radiothermometry associated with the development of new antennas are formulated. The tasks of further research aimed at creating new designs of conformal antennas and antenna arrays aimed at improving the characteristics and expanding the functionality of medical radiothermographs are formulated.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.592
Threshold uncertainty score0.324

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 science0.0010.000
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 head0.018
GPT teacher head0.246
Teacher spread0.229 · 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