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Record W4408387803

Successful treatment of infraspinatus tendon-bursa ossification in a Labrador retriever.

2025· article· en· W4408387803 on OpenAlexaffabout
Sophie Cormillot, Colin W. Sereda

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsGuardian Chemicals (Canada)
Fundersnot available
KeywordsLabrador RetrieverMedicineAnatomyOssificationTendonSurgery
DOInot available

Abstract

fetched live from OpenAlex

physical and orthopedic examination in addition to computed tomographic imaging. The dog underwent medical treatment involving rest, controlled exercise, deracoxib, shockwave therapy, and intra-articular glucocorticoid injections without success before surgical correction. Surgical treatment involved resection of the mineralized material and tenectomy of the infraspinatus insertion on the proximal humerus. The dog's lameness and pain resolved completely after surgery and the dog continues to experience no lameness or pain 7 mo post-surgery. Key clinical message: The successful surgical treatment of mineralization of the tendon and bursa of the infraspinatus muscle in a dog is described. The diagnostic approach, treatment, and clinical outcome are detailed to provide a reference for the potential treatment of future cases.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.298
Teacher spread0.273 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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