COMPARISON BETWEEN CRANIAL THORACIC INTERVERTEBRAL DISC HERNIATIONS IN GERMAN SHEPHERD DOGS AND OTHER LARGE BREED DOGS
Bibliographic record
Abstract
Cranial thoracic intervertebral disc herniations have been reported to be rare in dogs due to the presence of the intercapital ligament, however some studies have proposed they may not be uncommon in German Shepherd dogs. The purpose of this retrospective study was to compare cranial thoracic intervertebral disc herniations in German Shepherd dogs and other large breed dogs (control group). Medical records at the Ontario Veterinary College were searched for German Shepherd dogs and other large breed dogs that had magnetic resonance imaging studies including the T1-T9 region. For each dog and each disc space from T1-T9, three variables (compression, disc degeneration, and herniation) were recorded and graded based on review of sagittal T2-weighted images. Twenty-three German Shepherd dogs and 47 other large breed dogs met inclusion criteria. The German Shepherd dog group had higher scores than the control group for compression (P = 0.0099) and herniation (P < 0.001), but not disc degeneration (P = 0.97). In the German Shepherd dog group, intervertebral discs T2-T3 and T4-T5 had an increased risk for compression and T3-T4 had an increased risk for compression and herniation. Findings from this study indicated that German Shepherd dogs may be more likely than other large breed dogs to have spinal cord compression due to cranial thoracic disc herniations. Imaging of the cranial thoracic spine, including T2-T3, is recommended for German Shepherd dogs with T3-L3 neurological signs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".