Cross-Reality Lifestyle: Integrating Physical and Virtual Lives Through Multiplatform Metaverse
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
Technological advances are redefining the relationship between physical and virtual spaces. Traditionally, when users engage in virtual reality, they are completely cutoff from the physical space. Similarly, they are unable to access virtual experiences while engaged in physical activities. However, modern multiplatform metaverse environments allow simultaneous participation through mobile devices, creating new opportunities for integrated experiences. This study introduces the concept of “cross-reality lifestyles” to examine how users actively combine their physical and virtual activities. We identify three patterns of integration: first, Amplification: one space enhances experiences in the other; second, Complementary: spaces offer different but equally valuable alternatives, and third, Emergence: simultaneous engagement creates entirely new experiences. We propose the ACE cube framework that analyzes these patterns as continuous characteristics, and by integrating this analysis with technical requirements of commercial platforms, we provide practical guidelines for platform selection, technical investment prioritization, and cross-reality application development.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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