Impact of Video Advertising on Driver Fixation Patterns
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
To assess driver distraction because of video advertising signs, eye fixation data were collected from subjects who passed four video advertising signs, three at downtown intersections and one on an urban expressway. On average, drivers glanced at the signs on 45% of the occasions on which the signs were present. When drivers looked, they made 1.9 glances, on average, with an average duration per glance of 0.48 s. The distribution of eye fixations on intersection approaches where video signs were visible was compared with that on approaches on which video signs were not visible. No significant differences were found in the number of glances made at traffic signals or street signs. On the video approach, a greater proportion of glances were made at the speedometer and rearview mirrors. Glances were made at short headways and occasionally in unsafe circumstances. In the downtown area, glances at static commercial signs were made at larger angles and at shorter headways than was the case for video signs. A comparison of the results with those of other studies showed that video signs were less likely to be looked at than traffic signs (about half the time versus virtually every time, respectively) and that individual average glance durations and total durations were similar to those found for traffic signs in rural environments. These results apply to particular video signs in particular environments. Another on-road study indicates that a video sign on a curve that is close to the line of sight and visible for an extensive period is particularly distracting.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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