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Record W3159955674 · doi:10.11159/eee19.115

Right-Angled Differential Transmission Line Using Un-ChamferedInductive Layout

2019· article· en· W3159955674 on OpenAlexvenueno aff
Chia-Han Chang, Wenju Chen, Chun-Long Wang

Bibliographic record

VenueProceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2019
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsnot available
FundersMinistry of Science and Technology, Taiwan
KeywordsComputer scienceLine (geometry)Transmission lineDifferential (mechanical device)Electric power transmissionMathematicsElectrical engineeringEngineeringGeometryTelecommunications

Abstract

fetched live from OpenAlex

In this paper, the right-angled differential transmission line, the right-angled differential transmission line using the chamfered inductive layout, and the right-angled differential transmission line using the un-chamfered inductive layout are presented and compared.The right-angled differential transmission line has a very large value of differential-to-common mode conversion, which is found to be -7.27dB from 0.1 GHz to 5.5 GHz.By using the chamfered inductive layout, the differential-to-common mode conversion can be kept below -14.75 dB from 0.1 GHz to 5.5 GHz.By using the un-chamfered inductive layout, the differential-to-common mode conversion can be further kept below -21.70 dB from 0.1 GHz to 5.5 GHz.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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