MétaCan
Menu
Back to cohort
Record W2761224370 · doi:10.1364/ao.49.004791

Photonic bandgap fiber bundle spectrometer

2010· article· en· W2761224370 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

VenueApplied Optics · 2010
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsOpticsSpectrometerBundleMaterials sciencePhotonic crystalPhotonic-crystal fiberOptical fiberMultispectral imagePhotonicsOptoelectronicsPhysicsComputer science

Abstract

fetched live from OpenAlex

By using a photonic bandgap (PBG) fiber bundle and a monochrome CCD camera, we experimentally demonstrate an all-fiber spectrometer. A total of 100 Bragg fibers that have complementary and overlapping bandgaps are chosen to compose the fiber bundle. A monochrome CCD is then used to capture the binned image. To reconstruct the test spectrum from a single CCD image, we develop an algorithm based on pseudoinversion of the spectrometer transmission matrix. We demonstrate that the peak center wavelength can always be reconstructed within several percent of its true value regardless of the peak width or position, and that, although the widths of the individual Bragg fiber bandgaps are quite large (60-180nm), the spectroscopic system has a resolution limit of approximately 30nm. Moreover, we conclude that, by minimizing system errors, the resolution can be further improved down to several nanometers in width. Finally, we report fabrication of PBG fiber bundles containing hundreds of fibers using a two-stage drawing technique. This method constitutes a very promising approach toward industrial-strength fabrication of all-fiber spectrometers.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score0.999

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)0.0170.002

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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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