GIS Based Surveillance of Road Traffic Accidents (RTA) Risk for Rawalpindi City: A Geostatistical Approach
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
Identification of previously existing traffic accident hotspots is the first step to ensure future road safety. The present study focused on providing GIS based geostatistical surveillance for the Road Traffic Accidents (RTA) in Rawalpindi for five years (2009-2013) to determine the high risk areas or hotspots. For this purpose, spatial autocorrelation (Moran’s I test), Standard Deviational Ellipse (SDE) and hotspot (Getis-Ord Gi*) analyses were performed on the data obtained from Punjab Emergency Service Department (Rescue 1122). Spatial clusters and hotspots identified during the research lied mostly in the Northern and Northeastern part of the study area encompassing both commercial and residential areas of the city with majority of accident hotspots being near schools, hospitals, airport and highways. The study proposed that serious steps should be taken to improve the road safety conditions in these areas and focus of Emergency Response Providers (ERPs) should be directed there. Furthermore, the integration of GIS based expertise in the Emergency department should be ensured for regular surveillance of shifts in hotspots.
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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 | 0.001 | 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