The Effect of Compression Applied Through Constrained Lateral Eccentricity on the Failure Mechanics and Flexibility of the Human Cervical Spine
Bibliographic record
Abstract
In contrast to sagittal plane spine biomechanics, little is known about the response of the cervical spine to axial compression with lateral eccentricity of the applied force. This study evaluated the effect of lateral eccentricity on the kinetics, kinematics, canal occlusion, injuries, and flexibility of the cervical spine in translationally constrained axial impacts. Eighteen functional spinal units were subjected to flexibility tests before and after an impact. Impact axial compression was applied at one of three lateral eccentricity levels based on percentage of vertebral body width (low = 5%, medium = 50%, high = 150%). Injuries were graded by dissection. Correlations between intrinsic specimen properties and injury scores were examined for each eccentricity group. Low lateral force eccentricity produced predominantly bone injuries, clinically recognized as compression injuries, while medium and high eccentricity produced mostly contralateral ligament and/or disc injuries, an asymmetric pattern typical of lateral loading. Mean compression force at injury decreased with increasing lateral eccentricity (low = 3098 N, medium = 2337 N, and high = 683 N). Mean ipsilateral bending moments at injury were higher at medium (28.3 N·m) and high (22.9 N·m) eccentricity compared to low eccentricity specimens (0.1 N·m), p < 0.05. Ipsilateral bony injury was related to vertebral body area (VBA) (r = -0.974, p = 0.001) and disc degeneration (r = 0.851, p = 0.032) at medium eccentricity. Facet degeneration was correlated with central bony injury at high eccentricity (r = 0.834, p = 0.036). These results deepen cervical spine biomechanics knowledge in circumstances with coronal plane loads.
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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 | 0.000 | 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) | 0.002 | 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".