MétaCan
Menu
Back to cohort
Record W2765595657 · doi:10.1109/isemc.2017.8077865

Study of fiberweave effect through simulation and measurement on performance of differential stripline at high frequency

2017· article· en· W2765595657 on OpenAlexaff
Nasser Ghassemi, Wenqian Han, Hugues Tournier

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsCiena (Canada)
Fundersnot available
KeywordsStriplineCable glandMaterials scienceSubstrate (aquarium)FiberOpticsAcousticsElectronic engineeringOptoelectronicsElectrical engineeringEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

Investigation on simulation and measurement of fiber-weave effect on performance of a differential stripline at high frequency is presented in this paper. Meg 4 substrate with 2x1067 fiber-weave is used to fabricate a 4.1 inch differential stripline on a 4 mil substrate. This paper shows the benefits of routing with at least 10 degree angle. Even by using a dense 2x1067 fiber-weave, if two fibers place on top of each other, routing in 0 degree can create 3.6 Ps/inch delay between P and N on a differential stripline, which can create a deep notch on insertion loss of 4.1 inch differential stripline at 31 GHz. To be able to do the measurement, a 2.92mm - K connector - to stripline transition is designed. Then a wide band TRL calibration kit was used to de-embed the break-out traces and the K-connector from the S parameter measurements. Frequency and time domain measurement and simulation results have acceptable correlation. A high resolution confocal microscope with x100 magnification is used to measure the dimension of fiber-weave to be able to do an accurate simulation.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.278

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 head0.036
GPT teacher head0.267
Teacher spread0.231 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicSemiconductor Lasers and Optical DevicesFrench-language works237,207