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Record W2604487083 · doi:10.1016/j.jcrs.2017.04.004

Iris suture fixation: Push-knot needle

2017· article· en· W2604487083 on OpenAlexaff
Fei Liu, Qiang Zhou, Charles Q. Yu, Victor H. Guaiquil, Yu Geng, Mark I. Rosenblatt

Bibliographic record

VenueJournal of Cataract & Refractive Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsCAE (Canada)
FundersNational Eye Institute
KeywordsIRIS (biosensor)Knot (papermaking)Fixation (population genetics)CannulaMedicineFibrous jointSurgeryOphthalmologyAnatomyMaterials scienceComputer scienceComputer vision

Abstract

fetched live from OpenAlex

We describe a technique to create a locking knot for iris reconstruction or intraocular lens fixation. A modified needle is prepared by straightening the tip of an ophthalmic viscosurgical device needle or a lacrimal cannula needle. After the suture is passed through 2 sides of an iris defect, the 2 ends are externalized and looped. One strand is then inserted into the needle from the tip out of the ferrule, and the knot is pushed into the anterior chamber by this needle in a controllable manner. Two other locking knots are then made by repeating the process. With this method, only 1 small corneal incision is necessary regardless of the number of knots required and only a small amount of anterior chamber space is needed during the knotting process.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.316
Teacher spread0.283 · 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 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

Citations2
Published2017
Admission routes1
Has abstractyes

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