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Record W1795858148 · doi:10.1364/ol.33.002479

High-speed, high-resolution Fourier-domain optical coherence tomography system for retinal imaging in the 1060 nm wavelength region

2008· article· en· W1795858148 on OpenAlexaff
Prabakar Puvanathasan, Peter Forbes, Zhao Ren, Doug Malchow, Shelley Boyd, Kostadinka Bizheva

Bibliographic record

VenueOptics Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsOptical coherence tomographyOpticsSuperluminescent diodeMaterials scienceRetinalRetinaPreclinical imagingChoroidPenetration depthPhysicsIn vivoMedicineOphthalmology

Abstract

fetched live from OpenAlex

A high-speed (47,000 A-scans/s), ultrahigh axial resolution Fourier domain optical coherence tomography (OCT) system for retinal imaging at approximately 1060 nm, based on a 1024 pixel linear array, 47 kHz readout rate InGaAs camera is presented. When interfaced with a custom superluminescent diode (lambda(c) = 1020 nm, Deltalambda = 108 nm, Pout = 9 mW), the system provides 3.3 microm axial OCT resolution at the surface of biological tissue, approximately 4.5 microm in vivo in rat retina, approximately 5.7 microm in vivo in human retina, and 110 dB sensitivity for 870 microW incident power and 21 mus integration time. Retinal tomograms acquired in vivo from a human volunteer and a rat animal model show clear visualization of all intraretinal layer and increased penetration into the choroid.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.207
Teacher spread0.194 · 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

Citations55
Published2008
Admission routes1
Has abstractyes

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