Virtual Rehearsal Suite: An Environment and Framework for Virtual Performance Practice
Bibliographic record
Abstract
Contemporary performance artists use Virtual Reality (VR) tools to create immersive narratives and extend the boundaries of traditional performance mediums. As the medium evolves, performance practice is changing with it. Our work explores ways to leverage VR to support the creative process by introducing the Virtual Rehearsal Suite (VRS) that provides users with the experience of a large-scale rehearsal or performance environment while occupying limited physical space and minimal real-world obstructions. In this paper, we discuss findings from scene study experiments conducted within the VRS. In addition, we contribute our thresholding protocols a framework designed to support user transitions into and out of VR experiences. Our integrated approach to digital performance practice and creative collaboration combines traditional and contemporary acting techniques with HCI research to harness the innovative capabilities of virtual reality technologies creating accessible, immersive experiences for actors while facilitating user presence through state change protocols.
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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 | 0.001 | 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 | 0.001 |
| 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".