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Record W2619295874 · doi:10.1109/nemo.2017.7964267

Air-Filled SIW interconnections for high performance millimeter-wave circuit and system prototyping and assembly

2017· preprint· en· W2619295874 on OpenAlexaff
Tifenn Martin, Frédéric Parment, Anthony Ghiotto, Tan‐Phu Vuong, Ke Wu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsInterconnectionPrinted circuit boardExtremely high frequencyInsertion lossRapid prototypingIntegrated circuit packagingElectronic circuitIntegrated circuitElectric power transmissionElectronic engineeringTransmission lineElectrical engineeringComputer scienceEngineeringTelecommunicationsMechanical engineering

Abstract

fetched live from OpenAlex

In this paper, the interconnection between two sections of Air-Filled Substrate Integrated Waveguide (AFSIW) transmission line is presented. AFSIW is of high interest for high performance and low-cost millimeter wave applications. It is based on multilayer Printed Circuit Board (PCB) process. For system prototyping and assembly, it is common to interconnect components and sub-circuits. However, to comply with stringent specifications, especially for space and aeronautical applications, connectors must be avoided as they directly impact the cost, the size and the loss. Also, transition from AFSIW to conventional transmission lines to implement conventional interconnect solutions will not be optimal in term of loss, size and power handling. Instead, in this paper, a direct interconnect between two AFSIW sections is studied. An experimental demonstration of the proposed interconnection shows a 0.29 dB insertion loss.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.221
Teacher spread0.193 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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