Awareness Affects the Response of Human Subjects Exposed to a Single Whiplash-Like Perturbation
Bibliographic record
Abstract
STUDY DESIGN: Human subjects were exposed experimentally to a single whiplash-like perturbation. OBJECTIVE: To determine how awareness of the presence and timing of a whiplash-like perturbation affects the onset and amplitude of the neck muscle response and the peak magnitude of head and neck kinematics. SUMMARY OF BACKGROUND DATA: Although most whiplash injuries are sustained in rear-end collisions, which occur without warning, most studies of whiplash injury have used subjects aware of the imminent perturbation. METHODS: Seated subjects (35 women and 31 men) underwent a single forward horizontal perturbation (peak acceleration, 1.5 g). Surface electromyography measured the sternocleidomastoid and cervical paraspinal muscle activity. Three awareness conditions were tested: a countdown for subjects alerted to their perturbation, a perturbation without an alert for subjects who expected it within 60 seconds, and an unexpected perturbation for surprised subjects who were deceived. RESULTS: The muscle and kinematic responses of aware (alerted and unalerted) subjects were not significantly different. Sternocleidomastoid activation occurred 7 ms later in surprised subjects than in aware subjects (P < 0.0002). Cervical paraspinal amplitudes were 260% larger and angular head accelerations in flexion were 180% larger in surprised male subjects than in alerted male subjects. Surprised female subjects exhibited a 25% larger head retraction and a 30% lower forward acceleration of the mastoid process than aware female subjects. CONCLUSIONS: The larger retractions observed in surprised females likely produce larger tissue strains and may increase injury potential. Aware human subjects may not replicate the muscle response, kinematic response, or whiplash injury potential of unprepared occupants in real collisions.
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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 | 0.000 | 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) | 0.002 | 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".