Use of magnetic resonance imaging for morphometric analysis of the caudal cranial fossa in Cavalier King Charles Spaniels
Bibliographic record
Abstract
OBJECTIVE: To perform morphometric analysis of the caudal cranial fossa in Cavalier King Charles Spaniels (CKCSs), to assess the relationship between caudal fossa dimensions and the frequency of magnetic resonance imaging (MRI) features of occipital abnormalities in CKCSs (with and without syringomyelia), and to compare caudal cranial fossa measurements in CKCSs with measurements of 2 groups of mesaticephalic dogs. ANIMALS: 70 CKCSs and 80 mesaticephalic (control) dogs. PROCEDURES: Dogs were placed into 4 groups as follows: Labrador Retrievers (n = 40), spaniel-type dogs (40; English Springer Spaniels and Cocker Spaniels), CKCSs with syringomyelia (55), and CKCSs without syringomyelia (15). Multiple morphometric measurements (linear, angular, and area) were obtained from cranial midsagittalT2-weighted magnetic resonance images including the brain and cervical portion of the spinal cord. Several specific MRI findings were also recorded for CKCSs that appeared to affect the occipital bone and cervicomedullary junction. RESULTS: No significant difference was identified among breeds in control groups and between sexes in any of the groups for all morphometric measurements. Significant differences were identified in CKCSs, compared with mesaticephalic dogs, in the area of the caudal cranial fossa and for several linear measurements that reflected the length of the ventral aspect of the occipital bone. These differences were greater in CKCSs with syringomyelia. All CKCSs had abnormalities in occipital bone shape. CONCLUSIONS AND CLINICAL RELEVANCE: CKCSs had a shallower caudal cranial fossa and abnormalities of the occipital bone, compared with those of mesaticephalic dogs. These changes were more severe in CKCSs with syringomyelia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.000 |
| 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".