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Record W4386128289 · doi:10.1109/pn58661.2023.10222976

Development of a Multifocal OCT Lens System and an Eye-Mimicking Phantom for Murine Eye Imaging

2023· article· en· W4386128289 on OpenAlexaff
Simon Brais-Brunet, Raphaël Maltais–Tariant, Caroline Boudoux, Mathieu Dehaes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustinePolytechnique Montréal
Fundersnot available
KeywordsImaging phantomLens (geology)RetinalOpticsEye lensContrast (vision)Optical imagingBiomedical engineeringOphthalmologyMedicinePhysics

Abstract

fetched live from OpenAlex

Retinal and vitreous imaging of the mouse eye can be used to study vascular retinal pathologies. This work presents a multifocal lens system allowing for deep axial field of view. To calibrate the lens system, an eye-mimicking optical phantom was developed and characterized. On this hemispherical phantom, an increase of averaged signal-to-noise ratio of 17 dB and averaged contrast improvement of 13 dB throughout the whole field of view were measured.

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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.287
Teacher spread0.262 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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