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Record W2094280182 · doi:10.1364/oe.22.000387

Fabrication of high quality, ultra-long fiber Bragg gratings: up to 2 million periods in phase

2014· article· en· W2094280182 on OpenAlex
Mathieu Gagné, Sébastien Loranger, Jérôme Lapointe, Raman Kashyap

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsOpticsFiber Bragg gratingMaterials scienceInterferometryFabricationReflectometryOptical fiberPhase modulationLong-period fiber gratingBandwidth (computing)PHOSFOSFiber optic sensorOptoelectronicsPlastic optical fiberPhase noisePhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

The fabrication and characterization of high quality ultra-long (up to 1m) fiber Bragg gratings (FBGs) is reported. A moving phase mask and an electro-optic phase-modulation (EOPM) based interferometer are used with a high precision 1-meter long translation stage and compared. A novel interferometer position feedback scheme to simplify the fabrication process is proposed and analyzed. The ultra-long uniform FBGs show near perfect characteristics of a few picometers bandwidth, symmetrical, near theory-matching group-delay and transmission spectra. Grating characterization using optical backscattering reflectometry and chirped FBGs are also demonstrated. Limitations of the schemes are discussed.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.770

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 head0.016
GPT teacher head0.288
Teacher spread0.272 · 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