Thoracolumbar spine mechanics contrasted under compression and shear loading
Bibliographic record
Abstract
The mechanical properties of the human spine have been studied extensively in compression, but there remains a lack of fundamental data in shear. The overall goal of this study was to contrast the mechanics of the thoracolumbar functional spinal unit (FSU) under compression and shear-type loads by evaluating endplate deformation, disc pressures, and kinematics between the different loading types. Eleven T12-L1 and one L1-L2 human FSUs were tested. Compression loads consisted of pure compression, extension-compression, flexion-compression, lateral left and right compression applied individually to a maximum of 500 N. Shear loading consisted of posterior, anterior, left, and right shear to a maximum of 500 N. Intervertebral motions, disc pressure, and vertebral body deformations were recorded for all loads. The deformations were measured using strain gauge rosettes at three points on the inferior vertebral body and one on the superior endplate of the inferior vertebra. The disc pressures and endplate deformations measured were significantly less in shear loading compared to compression and did not change significantly with the type of compression load. Vertebral rim strains were generally greater under shear loading compared with compression. The mechanics of load transfer in compression was the production of high disc pressures which were not linearly correlated with the central endplate deformation. In shear, the mechanism appears to be via the annulus fibrosus without the development of significant disc pressure. These differences between compression and shear loading may have implications for injury mechanisms in the thoracolumbar spine.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".