Measurements of Multimodal Approach to Haptic Interaction in Second Life Interpersonal Communication System
Bibliographic record
Abstract
The sense of touch has much importance in technology-mediated human emotion communication and interaction. Many researchers around the world are aiming to leverage the sense of touch in the communication medium between multiuser 3-D virtual world and real environment. Driven by the motivation, we explored the possibilities of integrating haptic interactions with Linden Lab's multiuser online virtual world, Second Life. We enhanced the open source Second Life viewer client in order to facilitate the communications of emotional feedbacks such as human touch, encouraging pat, and comforting hug to the participating users through real-world haptic stimulation. These emotional feedbacks that are fundamental to physical and emotional development in turn can enhance the users interactive and immersive experiences with the virtual social communities in the Second Life. In this paper, we describe the development of a prototype that realizes the aforementioned virtual-real communication through a haptic-jacket system. Some of the potential applications of the proposed approach includes distant lover's communication, remote child caring, and stress recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".