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Record W3091412513 · doi:10.1002/adpr.202000026

Ultracompact Lens‐Less “Spectrometer in Fiber” Based on Chirped Filament‐Array Gratings

2020· article· en· W3091412513 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Photonics Research · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsOpticsMaterials scienceCladding (metalworking)Fiber Bragg gratingFemtosecondSpectrometerOptical fiberPHOSFOSLong-period fiber gratingChirpGratingPhotonic-crystal fiberOptoelectronicsLaserLens (geology)Graded-index fiberFiber optic sensorPhysics

Abstract

fetched live from OpenAlex

Femtosecond laser irradiation is applied to a single‐mode optical fiber to embed a filament array through the silica cladding and guiding core and form chirped Bragg gratings. Unlike a planar‐shaped refractive index modification, the long and uniform filament facilitates efficient optical scattering into azimuthally narrowed radiation modes, external and transverse to the fiber cladding. Chirping of the grating period further provides spectral focusing. The combined spectral and azimuthal focusing permits lens‐less recording of bright and high‐resolution spectra spanning across most of the visible band with a low‐cost charged coupled device camera. The flexible point‐by‐point writing enables fiber tapping of light with engineered spectral and geometric focusing properties, permitting the design of new compact photonic devices based on the all‐fiber spectrometer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.060
GPT teacher head0.327
Teacher spread0.266 · 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