EVALUATION OF TWO METHODS OF PROMPTING DRIVERS TO USE SPECIFIC EXITS ON CONFLICTS BETWEEN VEHICLES AT THE CRITICAL EXIT
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
The Florida Department of Transportation used a series of changeable-message signs that functioned as freeway guide signs to divert traffic to Universal Theme Park via one of two eastbound exits based on traffic congestion at the first of the two exits. An examination of crashes along the entire route indicated a statistically significant increase in crashes at the first eastbound exit following the actuation of the system. Furthermore, all of the crashes occurred in close proximity to the exit gore (the crosshatched area at exits that drivers are not supposed to enter or traverse) at the first exit. In Experiment 1, behavioral data were collected using an alternating treatments design. These data revealed that reassigning the exit signs was effective in producing a change in the percentage of drivers using each of the two exits. These data also showed that the reassignment of the theme park exit was associated with an increase in the percentage of motor vehicle conflicts that consisted of vehicles cutting across the exit gore. An analysis revealed that the method used for switching the designated or active theme park exit on the series of changeable-message signs led to the presentation of conflicting messages to some motorists, thus resulting in erratic driving behavior (cutting across the exit gore). In Experiment 2, the treatment evaluated the use of a phased method of switching the designated theme park exit to eliminate the delivery of conflicting messages. The new method for switching the designated theme park exit was not associated with an increase in motorists cutting across the exit gore.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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