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Record W2914674259 · doi:10.1088/1361-6501/aafd87

On-line temperature measurement using single-ended distributed cascading fiber Bragg gratings-based Brillouin optical fiber sensor

2019· article· en· W2914674259 on OpenAlexaff
Jin Xu, Rongping Wang, Adnane Cabani, Ping Xu

Bibliographic record

VenueMeasurement Science and Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNational Natural Science Foundation of China
KeywordsFiber Bragg gratingPHOSFOSMaterials scienceOpticsFiber optic sensorBrillouin zoneLine (geometry)Optical fiberFiberBrillouin scatteringOptoelectronicsPolarization-maintaining optical fiberPhysicsComposite materialMathematics

Abstract

fetched live from OpenAlex

In this study, we report a novel method of on-line distributed temperature measurement in optical fibers. The method is based on a cascading fiber Bragg gratings (FBGs) single-ended Brillouin optical time-domain analyzer (BOTDA). This proposal applies the cascading FBGs both as a reflector and an optical filter to improve the signal-to-noise ratio of the single-ended BOTDA. Experimental results show that a 75 km sensing range with 3 °C temperature resolution and 5 m spatial resolution are achieved.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.242
Teacher spread0.207 · 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.

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

Citations1
Published2019
Admission routes1
Has abstractyes

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