Estimation of AIS3+ thoracic injury risks of belted drivers in NASS frontal crashes
Bibliographic record
Abstract
Real-world field data from the 1988-2001 National Automotive Sampling System (NASS) — Crashworthiness Data System of the United States were examined. The abbreviated injury scale (AIS) was used to relate the injuries. Specifically, the AIS3 + thoracic injury rates of belted drivers in real-world frontal crashes in the United States were investigated. The research consisted of five steps. Firstly, aggregate NASS data (i.e. the total number of AIS3 + injured drivers across the entire crash speed domain) were collected for numerous frontal crash categories. These categories included: primary direction of force (11 o'clock, 12 o'clock and 1 o'clock), crash severity (barrier-like and not barrier-like), gender (men and women), age groups (13–49 and 50–97 years) and level of restraint (belt-only and belt + airbag). Secondly, to control for the effect of these categories and to introduce the effect of crash speed change ( V), a statistical model was constructed to fit the field data. The outcome variable was AIS3 + thoracic injury rate; the predictor variables were V and the aforementioned categories. Thirdly, the resulting logistic fit was compared with the original (unfitted) field data. Conclusions derived from the logistic fit of the field data were consistent with the aggregate NASS data, i.e. for like events: higher-speed crashes were associated with a higher injury risk than lower-speed crashes; higher-severity crashes were associated with a higher injury risk than lower-severity crashes; female drivers exhibited a higher risk than male drivers; older drivers exhibited a higher risk than younger drivers; age effects were more pronounced than the gender effects (e.g. aggregate risk ratios between men and women were about 1.5, whereas ratios between older and younger drivers ranged from 4.2 to 5.5); and belt-only drivers exhibited a higher risk than belted drivers with airbags. Fourthly, the fidelity of the logistic model was evaluated against numerous, published, point estimates of AIS3 + thoracic field injury rates. The correlations were deemed acceptable. Finally, as an example of the utility of the logistic fit results, a set of empirical AIS3 + thoracic risk curves for differing ages (13-49 versus 50-97 years) and genders (male versus women) were derived for belt-only drivers.
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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 | 0.000 | 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 | 0.000 |
| 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".