COMMUNICATING MULTILEVEL EVACUATION CONTEXT USING SITUATED AUGMENTED REALITY
Bibliographic record
Abstract
Abstract. Emergency preparedness is a fundamental component of a successful emergency management strategy. This includes a proactive communication strategy that informs all stakeholders of the emergency plan and helps translate that knowledge to real spaces. Communicating multilevel built environments can be difficult, as the architectural complexity creates problems for both visual and mental representations of networks in 3D space. Modern mobile technology offers emerging opportunities for emergency managers to develop and deploy 3D visualizations of multilevel spaces that preserve the topology of those spaces while adding the spatial context that allows the individual to better understand their position within it. In this paper, we present a collection of mixed reality (specifically augmented reality) geovisualizations that overcome the visual limitations associated with the traditional static 2D methods of communicating the evacuation plans of multilevel structures. We demonstrate how this technology can provide spatially contextualized 3D geovisualizations that promote spatial knowledge acquisition and support cognitive mapping. These geovisualizations are designed as a proactive emergency management tool to educate and prepare at risk populations prior to the occurrence of a hazardous event.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".