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Record W1770675474

Laser treatment of iris cysts in a flat coated retriever.

2014· article· en· W1770675474 on OpenAlexaboutno aff
A. Enache, P. Boydell, Iuliana Ionaşcu, Alexandru Şonea

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPolyamine Metabolism and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIRIS (biosensor)OphthalmologyTropicamideUveitisLabrador RetrieverCiliary bodySurgeryPupilOptics
DOInot available

Abstract

fetched live from OpenAlex

Uveal cysts are fluid filled structures arised from the iris or ciliary body commonly presented in certain breeds such as Golden retriever, Labrador retriever and Boston terrier. This report describes the clinical signs, the laser technique and the postoperative aspect for a Flat Coated Retriever with iris cysts. A 6 year-old, neutered male Flat Coated Retriever was referred to the Animal Medical Centre with a history of two pigmented masses in the anterior chamber. Ophthalmic examination of the right eye showed the presence of two highly pigmented iris cysts attached at the pupillary margin to the posterior iris. Nonsteroidal eye drops (ketorol tromethamine) and a course of oral meloxicam were initiated a week before the procedure. Under general anaesthesia the diode laser was used with an indirect ophthalmoscope headset and a 20 diopter lens. Preoperative atropine and proxymetacaine eye drops were applied. Diode laser was used to deflate the cysts. Initial pigment dispersion in the anterior chamber and on the surface of the lens was noted. Topical nonsteroidal, steroidal and antibiotics (dexamethasone, polymyxin and neomycin) eye drops were continued to control the secondary uveitis. Clinical progress was monitored and there was minimal postoperative aqueous flare with no ocular discomfort. Diode laser is an effective treatment of highly pigmented iris cysts.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.198

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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