Analyzing User Behaviour Patterns in a Cross-Virtuality Immersive Analytics System
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
Recent work in immersive analytics suggests benefits for systems that support work across both 2D and 3D data visualizations, i.e., cross-virtuality analytics systems. Here, we introduce HybridAxes, an immersive visual analytics system that enables users to conduct their analysis either in 2D on desktop monitors or in 3D within an immersive AR environment - while enabling them to seamlessly switch and transfer their graphs between modes. Our user study results show that the cross-virtuality sub-systems in HybridAxes complement each other well in helping the users in their data-understanding journey. We show that users preferred using the AR component for exploring the data, while they used the desktop to work on more detail-intensive tasks. Despite encountering some minor challenges in switching between the two virtuality modes, users consistently rated the whole system as highly engaging, user-friendly, and helpful in streamlining their analytics processes. Finally, we present suggestions for designers of cross-virtuality visual analytics systems and identify avenues for future work.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 it