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Record W3116941905 · doi:10.14405/kjvr.2020.60.4.233

Magnetic resonance imaging features of the biceps tendon rupture in a Labrador retriever dog

2020· article· en· W3116941905 on OpenAlexaboutno aff
Hyun-Ju Cho, Hojung Choi, Youngwon Lee

Bibliographic record

VenueKorean Journal of Veterinary Research · 2020
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetic resonance imagingMedicineLamenessBicepsAnatomyTendonOsteoarthritisBiceps tendonRadiographyTenosynovitisCoronal planeRadiologyPathologySurgery

Abstract

fetched live from OpenAlex

A five-year-old spayed female Labrador retriever presented with right forelimb lameness one day earlier. Radiographs and computed tomography of the right shoulder joint revealed conspicuous enthesophytes, bone cyst, and bone fragment at the intertubercular groove. Magnetic resonance imaging showed a loss of continuity of the biceps tendon and inhomogeneous hyperintense signal of the surrounding soft tissue and moderate synovial fluid on T2-and proton density-weighted images with contrast enhancement on the postcontrast T1-weighted images. The dog was diagnosed with tenosynovitis and biceps tendon rupture with osteoarthritis based on a comprehensive evaluation of the computed tomography and magnetic resonance imaging features.

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)0.000
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 score0.556
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.385
Teacher spread0.304 · 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
Published2020
Admission routes1
Has abstractyes

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