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Equine Articular Synovial Cysts: 16 Cases

2012· article· en· W2120690755 on OpenAlexaff
M. Lacourt, Melinda H. MacDonald, Yves Rossier, Sheila Laverty

Bibliographic record

VenueVeterinary Surgery · 2012
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversité de Montréal
FundersUniversity of California, Davis
KeywordsMedicineLamenessPalpationHorseSurgeryPopliteal cystSynovial fluidCystSynovial cystOsteoarthritisRadiographyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To report the clinical findings, diagnosis, treatment and outcome of equine patients with articular synovial cysts. STUDY DESIGN: Retrospective case series. ANIMALS: Horses (n = 16) with articular synovial cysts. METHODS: Horses diagnosed with articular synovial cysts (1988-2009) at 2 veterinary teaching hospitals were studied. Signalment, history, clinical signs, diagnostic methods and treatment were retrieved and telephone follow-up was obtained. RESULTS: Sixteen horses with articular synovial cysts were identified. Lameness was the reason for referral in most (n = 9) horses. Diagnosis was based on a combination of palpation and imaging studies, including radiography, ultrasonography and/or arthrography. Excision of the cyst was performed in 8 horses. Outcome was available for 4 surgically and 2 conservatively treated horses. Lameness resolved in 3 horses treated surgically and the 4th died for unrelated reasons. The 2 conservatively treated horses performed satisfactorily for the rest of their career. CONCLUSIONS: Equine articular synovial cysts are rare and can be associated with lameness. The cysts had a synovial lining in all horses where it was assessed. Surgical excision may be successful in resolving the lameness and allowing selected horses to return to work.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.265
GPT teacher head0.409
Teacher spread0.144 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations7
Published2012
Admission routes1
Has abstractyes

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