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Record W2605758253 · doi:10.1117/12.2253170

Cellular structure of the healthy and keratoconic human cornea imaged in-vivo with sub-micrometer axial resolution OCT (Conference Presentation)

2017· article· en· W2605758253 on OpenAlexaff
Kostadinka Bizheva, Bingyao Tan, Erik Mason, Kirsten Carter, Lacey Haines, Luigina Sorbara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStromaKeratoconusCorneaStromal cellEpitheliumCorneal epitheliumMaterials scienceAnatomyPathologyOpticsOphthalmologyMedicinePhysicsImmunohistochemistry

Abstract

fetched live from OpenAlex

Keratoconus causes progressive morphological changes in the corneal epithelium (EPI), Bowman’s membrane (BM) and anterior stroma. However, it is still not well understood if KC originates in the corneal epithelium and propagates to the anterior stroma through disruptions of the BM, or vice versa. In this study we used a sub-micrometer axial resolution OCT system to image in-vivo the cellular structure of the EPI layer and the fibrous structure of the BM and the anterior stroma in mild to advanced keratoconics, as well as healthy subjects. The imaging study was approved by the University of Waterloo Human Research Ethics Committee. The OCT system operates in the 800 nm spectral region at 34 kHz image acquisition rate and provides 0.95 um axial and < 2 um lateral resolution in corneal tissue, which is sufficient to visualize the cellular structure of the corneal epithelium and the fibrous structure of the BM. In some subjects, localized thinning and thickening of the EPI layer was observed, while there was no visible damage to the BM or anterior stroma. In other subjects, localized breakage of the stromal collagen fibrils was observed with no significant morphological changes of the corneal EPI.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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