MétaCan
Menu
Back to cohort

CAD model for circuit parameters of superconducting-based hybrid planar transmission lines

2009· article· en· W2100321056 on OpenAlexaff
Hamid Reza Mohebbi, A. Hamed Majedi

Bibliographic record

VenueSuperconductor Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConductorCoplanar waveguidePlanarTransmission lineElectric power transmissionMicrostripSuperconductivityElectrical conductorCharacteristic impedanceComputer scienceCADTopology (electrical circuits)Line (geometry)Transmission (telecommunications)Materials sciencePhysicsOpticsElectrical engineeringCondensed matter physicsTelecommunicationsGeometryEngineering drawingComposite materialMicrowaveEngineering

Abstract

fetched live from OpenAlex

Using the concept of surface impedance associated with a superconductor or normal conductor's plate, we extend the CAD (computer aided design) formalisms on modeling and simulation of superconducting and normal transmission lines (STL and NTL) in order to include hybrid transmission lines (HTL). STL and NTL are entirely made of superconductor or normal conductor materials, respectively. In this paper, HTL refers to a planar transmission line (TL) such as parallel plate (PPTL), microstrip (μTL) and coplanar waveguide (CPW) whose ground plate is superconducting and whose top/center strip is a normal conductor or vice versa. We develop and present a set of closed-form equations in a tidy and succinct form for each configuration (STL, NTL and HTL) for widely-used planar TLs (PPTL, μTL and CPW). They can be easily implemented in a systematic way by the user for the purpose of fast TL design. The results obtained with this CAD tool are compared with previously reported results in the literature, and good agreement is observed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.025
GPT teacher head0.234
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations14
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueSuperconductor Science and TechnologySame topicMicrowave Engineering and WaveguidesFrench-language works237,207