Developmental anomalies of the lateral portion of the cervical neural arch: Multimodal imaging and clinical implications
Bibliographic record
Abstract
OBJECTIVE: This study aimed to describe the imaging spectrum of developmental anomalies of the lateral portion of the cervical neural arch. METHOD: This was a five-year retrospective review of consecutive computed tomography (CT) scans of the cervical spine for structural anomalies of the cervical vertebral pedicle and facets. CT, radiographs and, when available, magnetic resonance imaging studies were independently reviewed. Anomalies were grouped into the following three categories: the absence of a pedicle, clefts in the vertebral arch or isolated dysmorphism of the facet. Clinical data on demographics and neurological outcomes were documented. RESULTS: Among 9134 consecutive patients undergoing a CT scan of the cervical spine, 18 (0.2%) patients were found to have developmental anomalies of the pedicle and facets. Findings included 7/18 (39%) with congenital absence of a pedicle, 8/18 (44%) with clefts in the vertebral arch and 3/18 (17%) with isolated dysmorphism of the articular facets. No acute neurological deficits or spinal cord injuries were reported. Associated chronic symptoms included neck pain 10/18 (56%), radiculopathy 7/18 (39%) and myelopathy 1/18 (6%). CONCLUSION: Developmental anomalies of the pedicle and facet may mimic traumatic spinal pathologies. Recognising a diverse spectrum of imaging findings is vital to prevent misdiagnosis and unnecessary intervention.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".