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Record W2132728400 · doi:10.1109/jlt.2006.886710

Modeling and Analysis of a Multilayer Dielectric Slab Waveguide With Applications in Edge-Coupled Terahertz Photomixer Sources

2007· article· en· W2132728400 on OpenAlexaff
Daryoosh Saeedkia, Safieddin Safavi‐Naeini

Bibliographic record

VenueJournal of Lightwave Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTerahertz radiationMaterials scienceDielectricOpticsWaveguideOptoelectronicsPhotomixingTerahertz spectroscopy and technologyElectric fieldLaserSlabPhotocurrentFar-infrared laserTerahertz metamaterialsPhysics

Abstract

fetched live from OpenAlex

The waveguiding properties of a multilayer dielectric slab waveguide structure with applications in edge-coupled terahertz photomixer sources are studied. The structure guides two interfering laser beams, which their central frequency difference falls into the terahertz spectrum. The top layer of the dielectric waveguide structure is made of an ultrafast photoabsorbing material, wherein the power of the guided modes are being absorbed and converted into a terahertz signal. The optical field and power distributions inside the waveguide structure are studied for different physical parameters of the dielectric layers. The absorbed optical intensity and the generated terahertz photocurrent and terahertz power inside the photoabsorbing layer are calculated

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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 designSimulation or modeling
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

Citations12
Published2007
Admission routes1
Has abstractyes

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