Effects of reducing and enforcing speed limits in selected arterial roads in Bogota
Bibliographic record
Abstract
In Bogota, the speed limit in five corridors with the highest concentration of traffic crashes victims in the city was reduced from 60 to 50 km/h since November 2018. The average speed reduction in the corridors with speed management was 1.48 km/h during daytime and 3.04 km/h during nighttime. In arterial corridors without speed management, the average speed reduction was 0.7 km/h during daytime and 2.2 km/h during nighttime. The speed management measure influenced a reduction of 16.6% in the number of fatalities and an 10.5% increase of crashes with injuries. The severity of the crashes decreased. The average count of run over crashes was also reduced by 10%. Changes in the geographical distribution of crashes with injuries and fatalities along the corridors with speed management indicate the necessity to implement stricter enforcement measures to increase the effectiveness of speed management operations during nighttime.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".