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Record W2899994393 · doi:10.1109/jstqe.2018.2879015

Subwavelength Grating Waveguide Devices for Telecommunications Applications

2018· article· en· W2899994393 on OpenAlexafffund
Lawrence R. Chen, Junjia Wang, Behnam Naghdi, Ivan Glesk

Bibliographic record

VenueIEEE Journal of Selected Topics in Quantum Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaRoyal Society
KeywordsPhotonicsPhotonic integrated circuitGratingWaveguideElectronic circuitFiber Bragg gratingResonatorOptoelectronicsOptical filterSilicon photonicsSilicon on insulatorMaterials scienceOptical computingComputer scienceOpticsWavelengthSiliconElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Subwavelength grating (SWG) waveguides in silicon-on-insulator are emerging as an enabling technology for implementing compact, high-performance photonic integrated devices and circuits for signal processing and sensing applications. We provide an overview of recent work on developing wavelength selective SWG waveguide filters based on Bragg gratings, ring resonators, and contra-directional couplers, as well as optical delay lines for applications in optical communications and microwave photonics. These components increase the SWG waveguide component toolbox and can be used to realize more complex photonic integrated circuits with enhanced or new functionality.

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 score0.007
Threshold uncertainty score0.022

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

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