The impact of pedestrian countdown signals on single and two vehicle motor vehicle collisions: a quasi-experimental study
Bibliographic record
Abstract
The objective of this study was to examine the impact of pedestrian countdown signals (PCS) on the rate of motor vehicle collisions (MVCs) in Toronto, Canada. A quasi-experimental design was used to compare rates of single and two vehicle MVCs before and after installation of PCS in Toronto, Canada between January 2005 and December 2009. Collision incidence rates were compared using Poisson regression analyses with adjustment for relevant cofounders and reported as incidence rate ratios (IRR) with 95% confidence intervals (CI). Secondary analyses were performed on subsets of collisions by collision type and injury severity. A total of 94,175 MVCs occurred at or near 1965 intersections at which PCS were installed over the five-year study period. Overall, the MVC incidence rate increased 7.5% (IRR = 1.075; 95% CI: 1.042-1.109; p < 0.0001) after installation of PCS. The installation of PCS led to an increase in MVCs. PCS may have an unintended consequence of increasing the rate of MVCs.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".