Head and neck control varies with perturbation acceleration but not jerk: implications for whiplash injuries
Bibliographic record
Abstract
Recent studies have proposed that a high rate of acceleration onset, i.e. high jerk, during a low-speed vehicle collision increases the risk of whiplash injury by triggering inappropriate muscle responses and/or increasing peak head acceleration. Our goal was to test these proposed mechanisms at realistic jerk levels and then to determine how collision jerk affects the potential for whiplash injuries. Twenty-three seated volunteers (8 F, 15 M) were exposed to multiple experiments involving perturbations simulating the onset of a vehicle collision in eyes open and eyes closed conditions. In the first experiment, subjects experienced five forward and five rearward perturbations to look for the inappropriate muscle responses and 'floppy' head kinematics previously attributed to high jerk perturbations. In the second experiment, we independently varied the jerk ( approximately 125 to 3 000 m s(-3)) and acceleration ( approximately 0.65 to 2.6 g) of the perturbation to assess their effect on the electromyographic (EMG) responses of the sternocleidomastoid (SCM), scalene (SCAL) and cervical paraspinal (PARA) muscles and the kinematic responses of the head and neck. In the first experiment, we found neither inappropriate muscle responses nor floppy head kinematics when subjects had their eyes open, but observed two subjects with floppy head kinematics with eyes closed. In the second experiment, we found that about 70% of the variations in the SCM and SCAL responses and about 95% of the variations in head/neck kinematics were explained by changes in perturbation acceleration in both the eyes open and eyes closed conditions. Less than 2% of the variation in the muscle and kinematic responses was explained by changes in perturbation jerk and, where significant, response amplitudes diminished with increasing jerk. Based on these findings, collision jerk appears to have little or no role in the genesis of whiplash injuries in low-speed vehicle crashes.
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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 | 0.000 | 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) | 0.000 | 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".