MétaCan
Menu
Back to cohort
Record W2054013344 · doi:10.1364/ol.36.001990

Simultaneous dual-wavelength-band common-path swept-source optical coherence tomography with single polygon mirror scanner

2011· article· en· W2054013344 on OpenAlexaff
Youxin Mao, Shoude Chang, E. G. Murdock, Costel Flueraru

Bibliographic record

VenueOptics Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsNational Research Council CanadaInstitute for Microstructural Sciences
Fundersnot available
KeywordsOpticsOptical coherence tomographyScannerCoherence (philosophical gambling strategy)PhysicsWavelengthTomography

Abstract

fetched live from OpenAlex

We report a novel (to the best of our knowledge) simultaneous 1310/1550 two-wavelength band swept laser source and dual-band common-path swept-source optical coherence tomography (SS-OCT). Synchronized dual-wavelength tuning is performed by using two laser cavities and narrowband wavelength filters with a single dual-window polygonal scanner. Measured average output powers of 60 and 27 mW have been achieved for the 1310 and 1550 nm bands, respectively, while the two wavelengths were swept simultaneously from 1227 to 1387 nm for the 1310 nm band and from 1519 to 1581 nm for the 1550 nm band at an A-scan rate of 65 kHz. Broadband wavelength-division multiplexing is used for coupling two wavelengths into a common-path single-mode GRIN-lensed fiber probe to form dual-band common-path SS-OCT. Simultaneous OCT imaging at 1310 and 1550 nm is achieved. This technique allows for in vivo high-speed OCT imaging with potential application in functional (spectroscopic) investigations.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.199
Teacher spread0.185 · 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

Citations37
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueOptics LettersSame topicOptical Coherence Tomography ApplicationsFrench-language works237,207