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Record W2015433585 · doi:10.1159/000355415

Reverse Optic Capture to Stabilize a Toric Intraocular Lens

2013· article· en· W2015433585 on OpenAlex
Howard V. Gimbel, Anika Amritanand

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCase Reports in Ophthalmology · 2013
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsGimbel Eye Centre
Fundersnot available
KeywordsCapsulorhexisMedicineIntraocular lensCentrationLens (geology)Rotation (mathematics)Intraocular lensesOphthalmologyOptometrySurgeryComputer scienceOpticsVisual acuityComputer visionPhacoemulsificationPhysics

Abstract

fetched live from OpenAlex

PURPOSE: To describe a technique for stabilizing a rotationally unstable toric intraocular lens (IOL). METHOD: Case report and literature review. RESULTS: Surgical technique and long-term follow-up for a patient who underwent repositioning and stabilization of a mobile 1-piece acrylic toric IOL using reverse optic capture (ROC) are described. This patient presented with early, more than 70° off-axis rotation. The IOL was repositioned but was very mobile within the bag and tended to rotate off-axis; hence, it was stabilized in the desired position by capturing the optic through the anterior continuous curvilinear capsulorhexis, leaving the haptics in the bag. The immediate and 2-year postoperative follow-up revealed a stable and on-axis IOL with no visual, refractive or ocular complications. CONCLUSIONS: ROC is a useful and safe technique to address the problem of toric IOLs that tend to rotate at the time of surgery or are not stable postoperatively.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.023
GPT teacher head0.284
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