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Record W3026778654 · doi:10.3390/photonics7020033

Liquid-Filled Highly Asymmetric Photonic Crystal Fiber Sagnac Interferometer Temperature Sensor

2020· article· en· W3026778654 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

VenuePhotonics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceBirefringencePhotonic-crystal fiberInterferometryOpticsPolarization-maintaining optical fiberSensitivity (control systems)Atmospheric temperature rangeOptical fiberFiberFiber optic sensorGraded-index fiberSingle-mode optical fiberOptoelectronicsWavelengthComposite materialPhysics

Abstract

fetched live from OpenAlex

In this paper, we theoretically designed and numerically studied a high-resolution and ultrasensitive photonic crystal fiber temperature sensor by selective filling of a liquid with high thermo-optic coefficient in one of the airholes of the fiber. The finite element method was utilized to study the propagation characteristics and the modal birefringence of the fiber under different ambient temperatures. A large base birefringence value of 7.7 × 10−4 as well as a large birefringence sensitivity of almost 29% to a 10 °C temperature variation was achieved for the optimized fiber design with liquid chloroform between 15 °C and 35 °C. We also studied the performance of the proposed optical fiber in a temperature sensing Sagnac interferometer. An average linear temperature sensitivity of 17.53 nm/°C with an average resolution of 5.7 × 10−4 °C was achieved over a temperature range of 20 °C (15 °C to 35 °C).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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