Interaction Between Finite Helical Axes and Facet Joint Forces Under Combined Loading
Bibliographic record
Abstract
STUDY DESIGN: Finite element study. OBJECTIVE: To investigate the interaction between the finite helical axis and facet joint loads under combined loading. SUMMARY OF BACKGROUND DATA: Finite helical axes (FHA) in a functional spinal unit can indicate mechanical disorders and are relevant for the development of new arthoplasty techniques. The facet joints protect the intervertebral discs from excessive movements. The relationship between the FHAs and facet joint forces is not well-understood, because previous studies have separated both, spinal motion and facet forces. METHODS: A finite element model of a lumbar spinal segment L4-L5 was used to simulate axial compression load of 500 N together with moments starting from 0 to 7.5 Nm in single anatomic main planes. Load combinations of 7.5 Nm were generated by changing the load direction in steps of 15 degrees between each pair of the 3 anatomic mainplanes. RESULTS: For single axes loading, the FHAs were found to be in the center of the disc under small moments, independently from load directions. The facet joints were only slightly loaded. Higher moments increased the forces in facet joints up to 105 N in axial rotation, followed by extension (50 N) and lateral bending (36 N). Combined moments did not essentially increase the facet forces compared with the same moment applied in an anatomic main direction. High facet forces might have directed the FHAs to migrate posteriorly, especially for axial rotation. This situation resulted in FHAs outside the disc toward the compressed facet joint. CONCLUSION: For clinical practice, patients immediately after the operation, or patients with facet joint arthritis should reduce or avoid axial rotation alone or in combination with other load applications, especially axial rotation plus lateral bending or flexion.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".