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Record W2068811703 · doi:10.3390/fib2010092

Reliable Lifetime Prediction for Passivated Fiber Bragg Gratings for Telecommunication Applications

2014· article· en· W2068811703 on OpenAlex

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.

Bibliographic record

VenueFibers · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsWSP (Canada)
FundersDirection Générale de la Compétitivité, de l’Industrie et des Services
KeywordsFiber Bragg gratingMaterials sciencePHOSFOSOptical fiberFiberOptoelectronicsTelecommunicationsOpticsPlastic optical fiberComputer scienceFiber optic sensorComposite materialPhysics

Abstract

fetched live from OpenAlex

This paper is dedicated to the lifetime prediction of Type I Fiber Bragg gratings (FBG) and to problems that happen when stabilization (also called passivation) conditions or the industrial conditioning procedure depart from ageing ones (e.g., presence of hydrogen during the passivation process). For the first time, a reliable procedure to certify the predicted lifetime based on a “restricted” master curve built on real components (i.e., passivated FBG) is presented. It is worth noting that both procedures (master curve built on non-passivated or on passivated components) are based on the same model (demarcation energy approximation and the existence of a master curve) fed with ageing data (reflectivity decay vs. time and temperature). If the Master Curve (MC) build on passivated components can be derived from the original one, we can certify the lifetime prediction in a reliable manner.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.550
Threshold uncertainty score0.650

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 head0.221
Teacher spread0.214 · 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