Characterizing Lumbar Spine Kinematics and Kinetics During Simulated Low-Speed Rear Impact Collisions
Bibliographic record
Abstract
BACKGROUND: Recent work has demonstrated that low back pain is a common complaint following low-speed collisions. Despite frequent pain reporting, no studies involving human volunteers have been completed to examine the exposures in the lumbar spine during low-speed rear impact collisions. METHODS: Twenty-four participants were recruited and a custom-built crash sled simulated rear impact collisions, with a change in velocity of 8 km/h. Randomized collisions were completed with and without lumbar support. Inverse dynamics analyses were conducted, and outputs were used to generate estimates of peak L4/L5 joint compression and shear. RESULTS: Average (SD) peak L4/L5 compression and shear reaction forces were not significantly different without lumbar support (compression = 498.22 N [178.0 N]; shear = 302.2 N [98.5 N]) compared to with lumbar support (compression = 484.5 N [151.1 N]; shear = 291.3 N [176.8 N]). Lumbar flexion angle at the time of peak shear was 36° (12°) without and 33° (11°) with lumbar support. CONCLUSION: Overall, the estimated reaction forces were 14% and 30% of existing National Institute of Occupational Safety and Health occupational exposure limits for compression and shear during repeated lifting, respectively. Findings also demonstrate that, during a laboratory collision simulation, lumbar support does not significantly influence the total estimated L4/L5 joint reaction force.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".