Quantifying emergency response system risk caused by grade crossing blockages
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
Delays experienced by emergency response (ER) vehicles at highway-rail grade (level) crossings have potentially catastrophic consequences, but emerging technologies that provide crossing blockage information could mitigate risks to ER systems. While evidence suggests these technologies could reduce response times, there is a need to quantify the risk associated with crossing blockages on ER systems. This article develops and applies a probabilistic methodology to quantify this risk through two case examples using data collected in Winnipeg, Canada. The results show that 13.2% of ER vehicles that traversed the studied crossing experienced a crossing blockage delay in the study period. Likewise, 0.5% of ER trips dispatched from the studied station experienced a crossing blockage delay. City-wide aggregated results, produced by the arising software developed by TRAINFO, corroborated the findings of the probabilistic methodology. The methodology could be used to support real-time dispatching, to rank risky crossings, and to prioritize crossings for upgrades.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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