Anatomy and clinical significance of the uncinate process and uncovertebral joint: A comprehensive review
Bibliographic record
Abstract
INTRODUCTION: The uncinate process and its associated uncovertebral articulation are features unique to the cervical spine. This review examines the morphology of these unique structures with particular emphasis on the regional anatomy, development and clinical significance. MATERIALS AND METHODS: Five electronic databases were utilized in the literature search and additional relevant citations were retrieved from the references. A total of 74 citations were included for review. RESULTS: This literature review found that the uncinate processes and uncovertebral articulations are rudimentary at birth and develop and evolve with age. With degeneration they become clinically apparent with compression of related structures; most importantly affecting the spinal nerve root and vertebral artery. The articulations have also been found to precipitate torticollis when edematous and be acutely damaged in severe head and neck injuries. The uncinate processes are also important in providing stability and guiding the motion of the cervical spine. CONCLUSION: This review is intended to re-examine an often overlooked region of the cervical spine as not only an interesting anatomical feature but also a clinically relevant one.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".