Development and Validation of a Finite Element Model of the Occipito-Atlantoaxial Complex Under Physiologic Loads
Bibliographic record
Abstract
STUDY DESIGN: Numerical techniques were used to study the occipito-atlantoaxial complex. OBJECTIVES: To improve previous upper cervical spine finite element models and validate both the range of motion (ROM) and neutral zone of the model. SUMMARY OF BACKGROUND DATA: Finite element modeling is an important tool for studying the cervical spine. It has been theorized that the neutral zone may be a more sensitive parameter of spinal instability than ROM. However, the authors know of no published results by far that have validated the neutral zone of an occipito-atlantoaxial finite element complex. METHODS: An anatomic detailed, nonlinear finite element model based on the Visible Human Male data set was developed in this study. ROM and the neutral zone were compared with published experimental data in the analysis of the motions of each vertebral level under physiologic static loadings to simulate the movements of upper cervical spine under axial rotation, flexion, extension, and lateral bending. In addition, the loads of each ligament were also recorded. RESULTS: The moment-rotation relationship predicted by this model was apparently nonlinear, and the largest rotation was predicted in horizontal plane, followed by median plane and coronal plane. The ligaments across the complex were generally lax, and, therefore, the complex exhibited large ROMs and high proportions of the neutral zone to ROM. CONCLUSIONS: The findings from the validation of this newly developed model coincide with the experimental studies so that its application helps contribute to a more comprehensive understanding of the biomechanics of the craniocervical region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".