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Record W2317425650 · doi:10.1149/1.2355798

Performance Assessment of Ge-on-SOI-photodetector / Si-CMOS Receivers for High-Speed Optical Communications

2006· article· en· W2317425650 on OpenAlexaff
Steven J. Koester, Laurent Schares, Clint L. Schow, J.D. Schaub, G. Dehlinger, Fuad E. Doany, R. John, Jack O. Chu

Bibliographic record

VenueECS Transactions · 2006
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInfineon Technologies (Canada)
FundersDefense Advanced Research Projects Agency
KeywordsSilicon on insulatorPhotodiodeCMOSPhotodetectorDetectorOptoelectronicsMaterials scienceAmplifierSiliconElectronic engineeringComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper provides an assessment of the performance capabilities of infrared detectors and receivers using Ge-on- silicon-on-insulator (Ge-on-SOI) photodiodes and CMOS ICs. An overview of our recent results on these detectors is given, and an estimate of their performance capabilities based upon an optimized layer structure design is described. We also provide an overview of high-performance receivers that utilize Ge-on- SOI photodiodes paired with Si CMOS amplifier ICs, and describe the materials and integration challenges needed to be overcome in order to develop a full monolithically-integrated technology.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.503

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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 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

Citations0
Published2006
Admission routes1
Has abstractyes

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