Using Space Syntax to Enable Walkable AR Experiences
Bibliographic record
Abstract
"Walkable" Augmented Reality (AR) experiences span floors of a building or involve exploring city neighbourhoods. In these cases setting greatly impacts object placement, interactive events, and narrative flow: in a zombie game for example, a standoff might best occur in an open foyer while a chase might be most effective in a narrow hallway. Spatial attributes are important when experiences are designed for a specific setting but also when settings are not known at design time. In this paper we explore how generic spatial attributes can facilitate design decisions in both cases. We conduct game design through the lens of space syntax, illustrating how attributes like openness, connectivity, and visual complexity can assist placement of walkable AR content in a site-specific narrative-driven scavenger hunt called ScavengAR and a "site-agnostic" game called Adventure AR. We contribute a Unity3D plugin that resolves design constraints expressed in terms of space syntax attributes to place AR content for a single setting or for multiple settings dynamically.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".