Three-Dimensional Analysis of the Movement of Lumbar Spinal Nerve Roots in Nonsimulated and Simulated Adhesive Conditions
Bibliographic record
Abstract
STUDY DESIGN: Biomechanical analysis of the movement of the lumbar spinal nerve roots (NRs). OBJECTIVES: The characteristics of the movement of lumbar spinal NRs corresponding to the change of posture were three-dimensionally analyzed in nonsimulated and simulated adhesion conditions using a porcine model. SUMMARY OF BACKGROUND DATA: There is a paucity of data on the movement of NRs. MATERIALS AND METHODS: Thirty two NRs of four pig cadavers were investigated. (study 1) Two tantalum beads were sutured on respective NRs from L3 to L6. Five beads were put into each bony structure as reference points. The porcine body was put on the cage designed for three-dimensional radiostereometric analysis. Two oblique radiographs were simultaneously taken at flexion, neutral, and extension. (study 2) After study 1, either L4 NR was ligated onto the adjacent bone to mimic monoradicular adhesion. Radiographs were taken in the same manner. The movements of the beads on NRs relative to immobile standard points in each vertebra were analyzed. RESULTS: The movement of NRs was characterized as a combination of stretching/slackening and pendulum motion. The distance that NRs were stretched/slackened, the excursion, and the angles that NRs moved were: 0.39 +/- 0.29 mm, 1.81 +/- 0.63 mm, and 10.46 +/- 5.93 degrees (in nonadhesion), and 0.30 +/- 0.20 mm, 1.02 +/- 0.50 mm, and 7.13 +/- 3.79 degrees (in simulated adhesion), respectively. CONCLUSION: Adhesion might play a part in the pathogenesis of lumbar spinal disorders because mechanical irritation secondary to stretching/slackening and pendulum motion might be concentrated at the distal part of NRs, adjacent to adhesion site, which has less cerebrospinal fluid and is close to dorsal root ganglion.
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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 | 0.000 |
| 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) | 0.001 | 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".