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Record W2339382078 · doi:10.1364/ol.41.001881

Rapid high resolution imaging with a dual-channel scanning technique

2016· article· en· W2339382078 on OpenAlexfundno aff
Alberto de Castro, Gang Huang, Lucie Sawides, Ting Luo, Stephen A. Burns

Bibliographic record

VenueOptics Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsnot available
FundersNational Eye InstituteFoundation Fighting Blindness
KeywordsRaster scanOpticsFrame rateRaster graphicsChannel (broadcasting)Image resolutionTemporal resolutionResolution (logic)Materials sciencePhysicsComputer scienceComputer visionArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

A spatial shift between channels in a dual-beam raster-scan imaging system introduces a temporal separation between images from the two channels that can be much shorter than the frame rate of the system. The technique is demonstrated by measuring the velocity of erythrocytes in the retinal capillaries. We used an adaptive optics scanning laser ophthalmoscope and introduced a temporal separation between imaging channels of 4.7 ms. We imaged three subjects and measured changing capillary blood flow velocity at the pulse rate. Since the time shift between channels is easily and continuously adjustable, this method can be used to measure rapidly changing events in any raster scan system with little added complexity.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.194
Teacher spread0.186 · 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

Citations49
Published2016
Admission routes1
Has abstractyes

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