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Record W2158958406 · doi:10.2460/javma.240.1.69

Use of magnetic resonance imaging and histopathologic findings for diagnosis of an aneurysmal bone cyst in the scapula of a cat

2011· article· en· W2158958406 on OpenAlexaff
Jérôme Benamou, Bertrand Lussier, Kate Alexander, Malcolm J. Gains, Claudine Savard

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2011
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversité de MontréalAccelLab (Canada)
Fundersnot available
KeywordsScapulaMedicineMagnetic resonance imagingRadiographyRadiologyLamenessAneurysmal bone cystAmputationLesionSurgery

Abstract

fetched live from OpenAlex

CASE DESCRIPTION: An 18-month-old spayed female domestic shorthair cat was evaluated because of left thoracic limb lameness. CLINICAL FINDINGS: A firm mass was palpable in the left scapular region. On the basis of clinical signs; results of radiographic, ultrasonographic, and cytologic evaluations; and findings on magnetic resonance imaging, an aneurysmal bone cyst (ABC) of the scapula was strongly suspected. TREATMENT AND OUTCOME: Considering the large size of the mass and the poor prognosis for return to function of the left thoracic limb, amputation was elected. Histologic evaluation ruled out a malignant process and was diagnostic for ABC originating from the left scapula. The patient recovered well and was ambulatory the day after surgery. Three years after surgery, the cat was healthy. CLINICAL RELEVANCE: The combination of radiography, regional ultrasonography, and magnetic resonance imaging enabled lesion structure and cavity content evaluation. However, final diagnosis was confirmed by histologic evaluation. To our knowledge, this is the first veterinary report of the use of magnetic resonance imaging in the characterization and diagnosis of an ABC.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.077
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.076
GPT teacher head0.311
Teacher spread0.235 · 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

Citations18
Published2011
Admission routes1
Has abstractyes

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