Behavioral Measures of Copresence in Co-located Mixed Reality
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
When several people are co-located and immersed in a mixed reality environment, they may feel like they share the virtual environment or not. This feeling of copresence, along with its parent dimensions of social presence and presence, has been mostly studied by relying on subjective measures gathered through questionnaires. As a way to address the drawbacks of this approach, we introduce a protocol to gather behavioral measures in the context of co-located mixed reality. As a pair of participants avoid obstacles moving towards them, their errors, gaze, interpersonal distance, and timing are measured. By combining subjective measures gathered through a questionnaire drawing from previous studies on social presence with behavioral measures, we demonstrate new ways to assess how users experience copresence. We illustrate this protocol by evaluating the effect of visual feedback on collaborators' activity. The results of this experiment suggest the capability of our protocol by revealing the effect of visual feedback on both objective and subjective measures.
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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 | 0.000 | 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 it