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Record W2903313869 · doi:10.1109/tmtt.2018.2883601

A Novel Low-Temperature Superconductor Power Limiter

2018· article· en· W2903313869 on OpenAlexaff
Desireh Shojaei-Asanjan, Raafat R. Mansour

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2018
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLimiterMaterials scienceSuperconductivityElectrical engineeringPower (physics)High-temperature superconductivityOptoelectronicsCondensed matter physicsElectronic engineeringEngineering physicsPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper presents a novel concept for realizing an RF power limiter for protecting superconductor digital receivers. A lumped-element niobium (Nb)-based filter is used as a protection circuit. It consists of lumped-element resonators formed using spiral inductors and metal-insulator-metal capacitors integrated on a multilayer Nb process. The circuit operates as a filter at low-power levels and as a reflector at high-power levels. The lumped-element filter circuit is studied in detail to explain the performance of the filter at high-power levels. It is concluded that some of the lumped-element inductors switch from being inductors when operating at low-power levels to being capacitors when operating at high-power levels. When the lumped-element inductors switch to capacitors, the filter circuit that consists of LC resonators switches to a circuit that consists of capacitors, causing the input power to be reflected back. Both the theoretical and experimental results are presented to verify this phenomenon. In addition to applications in RF power limiters, the concept can be employed to realize transmit/receive (T/R) switches in order to isolate the (T/R) circuit from the receive circuit.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.014
Threshold uncertainty score0.691

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Labeled directly by 2 models reading the full record.

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

Citations6
Published2018
Admission routes1
Has abstractyes

Explore more

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