Ex vivo computed tomography evaluation of loading position on morphometry of the caudal cervical intervertebral disk spaces of dogs
Bibliographic record
Abstract
OBJECTIVE To provide an objective, quantitative morphometric description of the caudal cervical intervertebral disk (IVD) spaces of dogs. SAMPLE Vertebral specimens consisting of C4 through C7 from 5 medium-sized dogs. PROCEDURES CT images were obtained with the specimens positioned in neutral, flexion, extension, and lateral bending positions. Size and shape of the cranial and caudal end plates, angle between the end plates (IVD wedge angle), and craniocaudal distance (IVD width) between end plates for the 4 loading positions were measured and compared for the 3 segments (C4-5, C5-6, and C6-7). RESULTS End plate size and shape, IVD wedge angle, and IVD width were not significantly different among the 3 segments. Caudal cervical end plates were consistently larger than cranial cervical end plates. The IVD wedge angle ranged from -4.8° to 15.2°. Flexion induced a reduction in IVD width in the ventral portion of the IVD, whereas extension induced a decrease in width in the dorsal portion of the IVD. Central IVD width remained unchanged among the loading positions. CONCLUSIONS AND CLINICAL RELEVANCE Unique morphometric and dynamic characteristics of the caudal cervical IVD space of dogs were detected. These findings may help investigators when designing IVD prostheses for dogs with cervical spondylomyelopathy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".