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Record W2118698889

Broadband Ortho-Mode Transducer for high performance modular feed systems

2010· article· en· W2118698889 on OpenAlexaff
Uwe Rosenberg, Alexander Bradt, Michael Perelshtein, Patrice Bourbonnais

Bibliographic record

VenueEuropean Microwave Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsFocus Microwaves (Canada)
Fundersnot available
KeywordsBroadbandInterfacingTransducerCoaxialModular designBandwidth (computing)Computer sciencePolarization (electrochemistry)Data transmissionElectronic engineeringOpticsElectrical engineeringEngineeringTelecommunicationsPhysicsComputer hardware
DOInot available

Abstract

fetched live from OpenAlex

A high performance broadband Ortho-Mode Transducer (OMT) design with more than 70% bandwidth is based on a novel branching concept with a two-fold symmetric structure. A symmetrical pair of ridge waveguides is facing the common branching region serving one polarization. The orthogonal polarization is coupled by a symmetrical pair of probes associated with coaxial interconnections. Folded Magic Tees are implemented for the re-combination of the semi signal portions of the ridge waveguides and the coaxial interconnections, respectively, to serve the complete signal at the dedicated interface ports. (To overcome the bandwidth limitation of rectangular waveguide solutions, tailored ridge waveguides have been established for the interfacing and internal waveguide interconnections.) This broadband OMT is foreseen as the key building block in a modular feed system approach employed for high capacity data transmission with large radio antennae. The measured characteristics validate the design concept with the required high performance properties that are necessary for these outstanding applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2010
Admission routes1
Has abstractyes

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