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Record W2144268604 · doi:10.1109/jsen.2008.926186

Multiparameter Sensor Based on Single High-Order Fiber Bragg Grating Made With IR-Femtosecond Radiation in Single-Mode Fibers

2008· article· en· W2144268604 on OpenAlexaff
Dan Grobnic, Stephen J. Mihailov, Christopher W. Smelser, Robert B. Walker

Bibliographic record

VenueIEEE Sensors Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsFiber Bragg gratingMaterials scienceOpticsFemtosecondPHOSFOSNarrowbandFiber optic sensorSingle-mode optical fiberLong-period fiber gratingOptoelectronicsGratingOptical fiberLaserWavelengthPolarization-maintaining optical fiberPhysics

Abstract

fetched live from OpenAlex

Narrowband multiple high-order Bragg resonances from a single Bragg grating structure inscribed using a femtosecond IR laser and a 4.28 mum pitched phase mask are used to demonstrate a multiparameter sensor in standard low cutoff wavelength optical fiber. Six high reflectivity resonances that are observed in the wavelength range from 1 to 2 mum can be used to monitor up to six sensing parameters. Temperature and strain coefficients of the grating at each of the high-order Bragg resonances are evaluated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations20
Published2008
Admission routes1
Has abstractyes

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