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Record W2166187784 · doi:10.1109/tmtt.2008.2011247

Broadband Modeling of High-Frequency Microwave Devices

2009· article· en· W2166187784 on OpenAlex
D. Paul, M. Nakhla, Ramachandra Achar, Andreas Weisshaar

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 Transactions on Microwave Theory and Techniques · 2009
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsCarleton University
Fundersnot available
KeywordsEmphasis (telecommunications)BroadbandComputer scienceElectronic engineeringEquivalent circuitMicrowaveFrequency responseElectrical engineeringEngineeringTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Circuit modeling of high-frequency devices described by tabulated multiport parameters has generated immense interest during recent years. In most cases, equivalent circuit models (ECMs) are available to the designers, which correlate well with the measured parameters at lower frequencies, however, deviate at higher frequencies. Traditional efforts to improve ECMs are device specific, laborious, and <emphasis emphasistype="boldital">ad-hoc</emphasis> in nature. In order to address these difficulties, this paper presents an efficient and automated algorithm to identify appropriate frequency-dependent elements for adding to the ECM at arbitrary locations so as to correct for high-frequency errors. The new method enables the designers to retain their existing physical models while providing a means to capture the high-frequency effects accurately. </para>

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.747

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 head0.008
GPT teacher head0.218
Teacher spread0.211 · 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