Ossification off the infraspinatus tendon-bursa in 13 dogs
Bibliographic record
Abstract
Ossification of the infraspinatus tendon-bursa was diagnosed in 13 labrador retrievers, 12 of which were lame in one thoracic limb and the other in both. They ranged in age from 28 to 121 months (mean 69.4 months). The lameness developed gradually and was progressive in 11 of the 14 affected joints. Scapular muscle atrophy and signs of pain on direct pressure over the infraspinatus tendon of insertion were key clinical signs. Caudocranial radiographs revealed multiple mineralised masses lateral to the proximal humerus or glenohumeral joint in 11 of the 26 joints and single masses in 12. An arthroscopic examination revealed concomitant ligament or tendon abnormalities in six of seven shoulders. The dogs were followed up from one to 55 months (mean 20 months). of five shoulders treated with non-steroidal anti-inflammatory drugs (NSAIDS), one resolved, two improved and two were managed surgically. of six shoulders treated by the injection of long-acting intra-articular corticosteroid (five before and one after surgery), three resolved, two improved and one was unchanged. of six shoulders treated by the surgical resection of the infraspinatus tendon and bursa (three before and two after treatment with NSAIDs, and one after treatment with a long-acting intra-articular corticosteroid), four improved, one was unchanged and one was managed with an intra-articular long-acting corticosteroid. one shoulder was managed by restricted exercise and the lameness resolved. Histological examination of the excised tissues revealed heterotopic bone within the infraspinatus tendon and/or bursa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".