BIOMECHANICS OF CERVICAL SPINE FOLLOWING IMPLANTATION OF A SEMI-CONSTRAINED ARTIFICIAL DISC WITH UPWARD CENTER OF ROTATION: A FINITE ELEMENT INVESTIGATION
Bibliographic record
Abstract
The objective of this study was to evaluate the effects of a semi-constrained artificial disc with upward instantaneous center of rotation (ICR) on the biomechanics of the cervical spine. A three-dimensional nonlinear finite element model of the lower cervical spine (C4–C7) was developed using computed tomography (CT) data. The FE model was validated by comparing it to previously published experimental results for flexion-extension, lateral bending and axial rotation movements. The validated model was then altered to include prosthesis at the C5–C6 level. A hybrid test protocol was used to investigate the effects of total disc replacement. The results of this study showed that this artificial disc can help maintain the same range of motion (ROM) and intradiscal pressure as the intact model for most loading conditions. We also found that loads on the facet joints increased dramatically at index level. The capsular ligaments were also found to transmit more tension during flexion at implanted level. Although the artificial disc with upward ICR was found to restore normal kinematics, and prevented increases in intradiscal pressure, it was also associated with an overloading of the facet joints and capsular ligaments leading to potentially undesirable outcomes in the long term.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".