MétaCan
Menu
Back to cohort
Record W2068130108 · doi:10.1364/ao.51.007368

Tapered-fiber-based refractive index sensor at an air/solution interface

2012· article· en· W2068130108 on OpenAlexafffund
Ping Lü, Jérémie Harris, Xiaozhen Wang, Ganbin Lin, Liang Chen, Xiaoyi Bao

Bibliographic record

VenueApplied Optics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRefractive indexMaterials scienceOpticsCladding (metalworking)Cladding modeInterferometryGraded-index fiberOptical fiberAttenuationNormalized frequency (unit)Step-index profileFiber optic sensorMicrofiberPolarization-maintaining optical fiberOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

An approach to achieve refractive index sensing at an air and aqueous glycerol solution interface is proposed using a tapered-fiber-based microfiber Mach-Zehnder interferometer (MFMZI). Compared to a surrounding uniform medium of air or solutions, the spectral interference visibility of the MFMZI at the air/solution interface is significantly reduced due to a weak coupling between the fundamental cladding mode and high-order asymmetric cladding modes, which are extremely sensitive to the external refractive index. The MFMZI is experimentally demonstrated as an evanescent wave refractive index sensor to measure concentrations of glycerol solutions by monitoring average power attenuation of the tapered fiber.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.243
Teacher spread0.230 · 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

Citations31
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueApplied OpticsSame topicAdvanced Fiber Optic SensorsFrench-language works237,207