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
Abstract This paper presents a social agent pedestrian model based on experiments with human subjects. Research studies of criminology and environmental psychology show that certain features of the urban environment generate fear in people, causing them to take alternate routes. The Crime Prevention Through Environmental Design (CPTED) strategy has been implemented to reduce fear of crime and crime itself. Our initial prototype of a pedestrian model was developed based on these findings of criminology research. In the course of validating our model, we constructed a virtual environment (VE) that resembles a well‐known fear‐generating area where several decision points were set up. 60 human subjects were invited to navigate the VE and their choices of routes and comments during the post interviews were analyzed using statistical techniques and content analysis. Through our experimental results, we gained new insights into pedestrians' behavior and suggest a new enhanced and articulated agent model of a pedestrian. Our research not only provides a realistic pedestrian model, but also a new methodology for criminology research. Copyright © 2008 John Wiley & Sons, Ltd.
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 | 0.000 | 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 it