Autopsy Study of Motorcyclist Fatalities: The Effect of the 1992 Maryland Motorcycle Helmet Use Law
Bibliographic record
Abstract
OBJECTIVES: This study sought to determine the impact of Maryland's all-rider motorcycle helmet law (enacted on October 1, 1992) on preventing deaths and traumatic brain injuries among motorcyclists. METHODS: Statewide motorcyclist fatalities occurring during seasonally comparable 33-month periods immediately preceding and following enactment of the law were compared. RESULTS: The motorcyclist fatality rate dropped from 10.3 per 10 000 registered motorcycles prelaw to 4.5 postlaw despite almost identical numbers of registered motorcycles. Motorcyclists wearing helmets had a lower risk of traumatic brain injury than those not wearing helmets (odds ratio = 0.31, 95% confidence interval = 0.14, 0.68). CONCLUSIONS: Maryland's controversial motorcycle helmet law appears to be an effective public health policy and may be responsible for saving many lives.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".