MétaCan
Menu
Back to cohort
Record W2765477807 · doi:10.3390/s17112519

Femtosecond FBG Written through the Coating for Sensing Applications

2017· article· en· W2765477807 on OpenAlex
Joé Habel, Tommy Boilard, Jean-Simon Frenière, François Trépanier, Martin Bernier

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

VenueSensors · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsTeraXion (Canada)Université Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCoatingSiliconeFemtosecondFiber Bragg gratingCladding (metalworking)PolyimideComposite materialPHOSFOSFabricationLaserAcrylatePlastic-clad silica fiberAnnealing (glass)OptoelectronicsOpticsFiberPlastic optical fiberWavelengthFiber optic sensorPolymerLayer (electronics)

Abstract

fetched live from OpenAlex

Type I fiber Bragg gratings (FBG) written through the coating of various off-the-shelf silica fibers with a femtosecond laser and the phase-mask technique are reported. Inscription through most of the common coating compositions (acrylate, silicone and polyimide) is reported as well as writing through the polyimide coating of various fiber cladding diameters, down to 50 µm. The long term annealing behavior of type I gratings written in a pure silica core fiber is also reported as well as a comparison of the mechanical resistance of type I and II FBG. The high mechanical resistance of the resulting type I FBG is shown to be useful for the fabrication of various distributed FBG arrays written using a single period phase-mask. The strain sensing response of such distributed arrays is also presented.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.597

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 studies0.0010.000
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 head0.025
GPT teacher head0.277
Teacher spread0.252 · 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