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Record W2080528010 · doi:10.1149/1.2392920

Silicon Microphotonic Waveguide Technology for Sensing, Spectroscopy and Communications

2006· article· en· W2080528010 on OpenAlexaff
Siegfried Janz, Pavel Cheben, A. Delâge, A. Densmore, B. Lamontagne, E. Post, Jens H. Schmid, P. Waldon, Dan‐Xia Xu, K. P. Yap, W.N. Ye

Bibliographic record

VenueECS Transactions · 2006
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInstitute for Microstructural SciencesNational Research Council Canada
FundersGenomic Health
KeywordsWaveguideSilicon on insulatorNanometrePhotonicsSiliconSilicon photonicsOptoelectronicsSlow lightSpectroscopyMaterials scienceComputer scienceSlot-waveguideNanotechnologyElectronic engineeringOpticsPhysicsEngineeringPhotonic crystal

Abstract

fetched live from OpenAlex

The high index contrast of the silicon-on-insulator waveguide system gives the optical device designer a new ability to manipulate light at the nanometer scale, tailor the interaction of light with the local environment, and reduce overall device size. This paper describes some of the unique features of the Si microphotonic waveguide system, and some of the resulting applications and challenges encountered in working with this platform. The work of our group in addressing some of the more promising application in sensing, spectroscopy and communications is reviewed, along with our solutions to challenges encountered in making devices on the Si waveguide platform.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.406

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 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

Citations2
Published2006
Admission routes1
Has abstractyes

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