Motor vehicle crash reconstruction: Does it relate to the heterogeneity of whiplash recovery?
Bibliographic record
Abstract
Whiplash injury is a common consequence of motor vehicle crashes (MVC), yet it is also one of the most poorly understood. While more than 50% of those injured should expect to rapidly recover, others are not as fortunate with approximately 25% of those exposed to and injured in an MVC transitioning from acute to chronic pain and disability. The purpose of this prospective study was to determine if the severity and direction of collisions involving participants enrolled in a longitudinal study of recovery from whiplash are able to differentiate between different recovery groups based on the neck disability index (NDI) percentage scores at 3-months, and if these crash specific parameters are associated with known risk factors for recovery. Here, we examined objective collision data, repair invoices, and characteristics of the crash for 37 acutely injured participants consented and enrolled at their emergency department visit and further assessed at three time points; < 1 week, 2-weeks, and 3-months post MVC. Collision data were used to reconstruct and estimate the severity of the crash and determine if they aligned with the heterogeneity of whiplash injury recovery. Wilcoxon rank sum tests were used to determine if % scores on the Neck Disability Index (NDI) at 3-months post MVC were associated with the following variables: sex, head turned at time of impact, seatbelt use, whether or not airbags deployed, if the vehicle was struck while stopped or while turning, or the principle direction of force (PDOF). Spearman's correlation coefficients were used to determine if NDI at 3-months post MVC was associated with age, Body Mass Index, pain-related disability at baseline, signs of post-traumatic distress, intrusion/hyperarousal, negative affect, pain intensity, estimated speed change from the impact, and damage estimates (in US$). There was a significant positive association between self-reported neck disability at 3-months post MVC, post-traumatic distress, negative affect and uncontrolled pain. There was no direct effect of participant characteristics, arousal, intrusion/hyperarousal sub-score, damage, PDOF, speed change, or other crash characteristics. Established crash parameters were not associated with the heterogeneity of whiplash injury recovery in a small sample of injured participants.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".