Maxillofacial Injuries in Moose-Motor Vehicle Collisions Versus Other High-Speed Motor Vehicle Collisions
Bibliographic record
Abstract
BACKGROUND: Anecdotal experience has suggested that there is a higher frequency of maxillofacial injuries among motor vehicle collisions involving moose. OBJECTIVES: A retrospective cohort study design was used to investigate the incidence of various injuries resulting from moose-motor vehicle collisions versus other high-speed motor vehicle collisions. METHODS: A chart review was conducted among patients presenting to a Canadian regional trauma centre during the five-year period from 1996 to 2000. RESULTS: Fifty-seven moose-motor vehicle collisions were identified; 121 high-speed collisions were randomly selected as a control group. Demographic, collision and injury data were collected from these charts and statistically analyzed. The general demographic features of the two groups were similar. Moose collisions were typically frontal impact resulting in windshield damage. The overall injury severity was similar in both groups. Likewise, the frequency of intracranial, spinal, thoracic and extremity injuries was similar for both groups. The group involved in collisions with moose, however, was 1.8 times more likely then controls to sustain a maxillofacial injury (P=0.004) and four times more likely to sustain a maxillofacial fracture (P=0.006). CONCLUSIONS: Occupants of motor vehicles colliding with moose are more likely to sustain maxillofacial injuries than those involved in other types of motor vehicle collisions. It is speculated that this distribution of injuries relates to the mechanism of collision with these large mammals with a high centre of gravity.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".