Symbiotic Society with Avatars (SSA)
Bibliographic record
Abstract
Avatar robots can help people extend their physical, cognitive, and perceptual capabilities, allowing people to exceed time and space constraints. In that sense, avatar robots can greatly influence people's lives. However, we have many challenges to be addressed in various scenarios such as avatar-human interaction, operator-avatar interaction, avatar-avatar interaction, ethical and legal issues, technical challenges, and so on. It is indispensable to discuss what the necessary research and technologies are to realize avatars that are well accepted in society while envisioning a future symbiotic society in which people communicate with other people and their avatars. In our previous workshop "Symbiotic Society with Avatars: Social Acceptance, Ethics, and Technologies (SSA)" we focused on the ethical aspect of avatars. In this workshop, our aim is to provide an opportunity for researchers from different backgrounds including social robotics, teleoperation, and mixed reality to come together and discuss the advances and values in a symbiotic society with avatars.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".