Pregnancy and the risk of a traffic crash
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Pregnancy causes diverse physiologic and lifestyle changes that may contribute to increased driving and driving error. We compared the risk of a serious motor vehicle crash during the second trimester to the baseline risk before pregnancy. METHODS: We conducted a population-based self-matched longitudinal cohort analysis of women who gave birth in Ontario between April 1, 2006, and March 31, 2011. We excluded women less than age 18 years, those living outside Ontario, those who lacked a valid health card identifier under universal insurance, and those under the care of a midwife. The primary outcome was a motor vehicle crash resulting in a visit to an emergency department. RESULTS: A total of 507,262 women gave birth during the study period. These women accounted for 6922 motor vehicle crashes as drivers during the 3-year baseline interval (177 per mo) and 757 motor vehicle crashes as drivers during the second trimester (252 per mo), equivalent to a 42% relative increase (95% confidence interval 32%-53%; p<0.001). The increased risk extended to diverse populations, varied obstetrical cases and different crash characteristics. The increased risk was largest in the early second trimester and compensated for by the third trimester. No similar increase was observed in crashes as passengers or pedestrians, cases of intentional injury or inadvertent falls, or self-reported risky behaviours. INTERPRETATION: Pregnancy is associated with a substantial risk of a serious motor vehicle crash during the second trimester. This risk merits attention for prenatal care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it