Exploring road safety of pedestrians in proximity to public transit access points (bus stops and metro stations), a case study of Montreal, Canada
Bibliographic record
Abstract
Public transit plays a significant role in the sustainability of an urban region which requires high pedestrian safety at the interchange points. This research studies the magnitude of pedestrian collisions in the proximity of Public Transit Access Points (PTAPs) and address how Traffic Calming strategies and road elements improve pedestrian safety at PTAPs. Getis-Ord Hotspot Analysis and the Negative Binomial models are applied to address research questions. Pedestrian collisions occur more frequently at intersections with the presence of a PTAP and with a higher volume and number of bus routes. Traffic calming strategies such as road width reduction, sidewalk width increase, median refuges, pedestrian crossing phase, and vehicle stop signs could improve pedestrian safety of PTAP. Besides, pedestrians are at more risk in PTAP at locations where high road gradients and in proximity to intersections with a higher number of directions of vehicle traffic flow.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".