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Record W2331979611 · doi:10.1097/ico.0000000000000060

Modification of the Miyake–Apple Technique for Simultaneous Anterior and Posterior Video Imaging of Wet Laboratory–Based Corneal Surgery

2014· article· en· W2331979611 on OpenAlexaff
Johnson Tan, Howard Meadows, Aanchal Gupta, Sonia N. Yeung, Gregory Moloney

Bibliographic record

VenueCornea · 2014
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsVancouver Native Health SocietyUniversity of British Columbia
Fundersnot available
KeywordsDioptreMicroscopeComputer scienceCorneaBubbleOphthalmologyMedicineMaterials scienceBiomedical engineeringVisual acuity

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to describe a modification of the Miyake-Apple posterior video analysis for the simultaneous visualization of the anterior and posterior corneal surfaces during wet laboratory-based deep anterior lamellar keratoplasty (DALK). METHODS: A human donor corneoscleral button was affixed to a microscope slide and placed onto a custom-made mounting box. A big bubble DALK was performed on the cornea in the wet laboratory. An 11-diopter intraocular lens was positioned over the aperture of the back camera of an iPhone. This served to video record the posterior view of the corneoscleral button during the big bubble formation. An overhead operating microscope with an attached video camcorder recorded the anterior view during the surgery. RESULTS: The anterior and posterior views of the wet laboratory-based DALK surgery were simultaneously captured and edited using video editing software. The formation of the big bubble can be studied. CONCLUSIONS: This video recording camera system has the potential to act as a valuable research and teaching tool in corneal lamellar surgery, especially in the behavior of the big bubble formation in DALK.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

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

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 head0.253
Teacher spread0.239 · 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 teacher head, 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

Citations3
Published2014
Admission routes1
Has abstractyes

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