Analysis of Midblock Crashes in an Urban Divided Arterial Road
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
This study analyzes the crashes that occur at midblock called “midblock crashes” in an urban arterial road. The association of midblock crashes with various factors was examined using the 7-year (2000–2006) crash data on a section of a divided arterial road in Windsor, Ontario, Canada. To account for difference in traffic volume and road geometric factors between two directions of travel in a divided road, the data were collected for two directions separately. The results of log-linear models using these bidirectional data show that midblock crashes are more likely to occur on the road sections with access points and high percentage of trucks (>20%). The results of logistic regression models show that median opening, driver age/gender, lighting, time of day, and day of week are associated with different types of crashes classified by the vehicles involved in crashes. The study shows the importance of analyzing midblock crashes using the bidirectional data by vehicle type in urban divided arterial roads with high truck volume.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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