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Record W899584232

Cataracts: a summary and treatment via phacoemulsification

2004· article· en· W899584232 on OpenAlexaboutno aff
Kelly Lyboldt

Bibliographic record

VenueeCommons (Cornell University) · 2004
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsnot available
Fundersnot available
KeywordsPhacoemulsificationCataractsMedicineOptometryOphthalmology
DOInot available

Abstract

fetched live from OpenAlex

Cataracts, simply defined as a focal or complete opacification of the lens, are the leading cause of vision in purebred and older dogs. Caratacts can be congenital or acquired postnatally, inherited, or caused by disease, toxicity, trauma, or advanced age. Surgery is the only method of restoring vision in patients blinded by cataracts. The development of phacoemulsification in conjunction with the development of the artificial lens has greatly improved the success rate of the surgery, as well as the visual acuity post-operatively. A 3 year old, male castrated chocolate Labrador retriever presented with the chief complaint of vision loss in both eyes. The dog was bright, alert and responsive. He was over conditioned and aside from his vision loss his physical examination was unremarkable. Initial ophthalmic examination revealed that he had bilateral mature cataracts. His eyes appeared slightly microphthalmic and had iris-to-iris persistent pupillary membranes. Preoperative evaluation included hemogram and serum chemistry panel (both normal), electroretinography (normal) and ocular ultrasonography (normal). The opthalmic examination findings and ERG/US diagnostic results suggested his progressive cataracts had been congenital. This paper will briefly explore cataracts, their causes, and their differentiation from nuclear sclerosis. It will also take an in depth look at their surgical treatment by phacoemulsification with introcular lens implantation.

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)0.000
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 score0.410
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.031
GPT teacher head0.206
Teacher spread0.176 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

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