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Record W2946921380 · doi:10.1109/jlt.2019.2910204

Thermal Stability of Drawing-Tower Grating Written in a Single Mode Fiber

2019· article· en· W2946921380 on OpenAlexaff
Sai Liu, Liyun Ding, Huiyong Guo, Ai Zhou, Ciming Zhou, Li Qian, Haihu Yu, Desheng Jiang

Bibliographic record

VenueJournal of Lightwave Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMaterials scienceGratingFiber Bragg gratingOpticsThermalThermal stabilityOptical fiberGermaniumOptoelectronicsFiber laserFiberWavelengthSiliconComposite materialPhysics

Abstract

fetched live from OpenAlex

The thermal stability of drawing-tower grating (DTG) has become the primary concern in applications because of its great advantages in building a large-capacity distributed fiber grating sensing network. Different aging trainings were performed on the DTGs written by single laser pulses at 193 nm in a low-germanium doped silica fiber, and the thermal stability of Bragg wavelength and reflectivity at different temperatures were investigated to demonstrate that the DTG is reliable in some sensing applications. A double exponential function model is proposed as a method to study the decay characteristics of the DTG reflectivity.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.529

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 integrity0.0000.001
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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.

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

Citations15
Published2019
Admission routes1
Has abstractyes

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