Creating a Mixed Reality Retail Experience With Present Hardware Limitations
Bibliographic record
Abstract
<p>In the retail context, Virtual Reality is great for building prominent brand identity and spectacle experiences while Augmented Reality allows users to explore products in their own comfort zones thus increasing users' purchase intentions (Bogicevic et al., 2019, Heller et al., 2019, Hilken et al., 2021). This research investigates methodologies that can be used to create a mixed-reality retail experience by combining the best aspects of Augmented and Virtual Reality under one system. The accompanied experience utilizes the passthrough capabilities of the Oculus Quest 2 VR headset, which allows users to switch between being completely immersed in a virtual environment (VR) and being in their own environment while seeing virtual objects overlaid (AR) to create a system that can seamlessly switch between both worlds. Furthermore, the research explores designing interactions and elements that would be pertinent in both AR and VR scenarios to offer an immersive and engaging mixed-reality experience.</p>
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".