Robots as social companions for space exploration
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
Space is the next border that humanity needs to cross to reach new developments. Yet, space exploration faces numerous challenges, especially when it comes to hazard putting in danger human health. While a lot of efforts are being made to mitigate the impact of space travel on physical health, mental health of space travelers is also highly at risk, notably due to isolation and the associated lack of meaningful social interactions. Given the social potentiality of artificial agents, we propose here that social robots could play the role of social partners to mitigate the impact of space travel on mental health. We will explore the logics behind using robots as partners for in-space social training. We will then identify what are the advantages of using social robots for this purpose, either for crew members and passengers on shorter spaceflights, or for potential colons for possible future longer-term space exploration missions. • Space exploration faces numerous challenges. • Space travel negatively impacts human health. • Mental health of space travelers is at risk due to social isolation. • Social robots could mitigate the impact of space travel on mental health. • Robots could act as partners for in-space social training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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