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Record W2095181835 · doi:10.1364/oe.14.003152

Optimization of a continuous phase-only sampling for high channel–count fiber Bragg gratings

2006· article· en· W2095181835 on OpenAlexaff
Hongpu Li, Ming Li, Kazuhiko Ogusu, Yunlong Sheng, J. Rothenberg

Bibliographic record

VenueOptics Express · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsOpticsMaterials scienceChannel spacingFiber Bragg gratingChannel (broadcasting)Phase (matter)FabricationDiffractionOptoelectronicsWavelength-division multiplexingOptical fiberTelecommunicationsComputer sciencePhysics

Abstract

fetched live from OpenAlex

A novel continuous phase-only sampling function capable of producing up to 81-channel FBG with excellent channel uniformity and high in-band energy efficiency is presented and optimized by using the simulated annealing algorithm. In order to fabricate this kind of FBG with a conventional side-writing phase-mask technique, both the diffraction effects and fabrication tolerance of the phase-shifted phase mask have also been addressed. Compared with the numerical results, a 45-channel (spacing 100 GHz) and an 81-channel (spacing of 50 GHz) phase-only sampled linearly chirped FBG are successfully demonstrated.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.309
Threshold uncertainty score0.982

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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
GenreMethods

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

Citations28
Published2006
Admission routes1
Has abstractyes

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