Analysis of body motion synchrony phenomenon in communities and between communities
Why this work is in the frame
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Bibliographic record
Abstract
We evaluate community activity in social network based on body motion synchrony of two people during face-to-face communication. In particular, we look at people's body motion synchrony when they are in the same communities and from different communities. Using wearable sensors, we measured individuals' time series body motion data and face-to-face communication data. From these data we detected communities in 6 organizations and statistically analyze the distribution of body motion rhythm difference in communities and between communities. The result showed the tendency that people who are in the same communities are easier to synchrony than people who are from different communities. Moreover, we make comparison on the result based on two different community detection methods. One detection method is based on real department information, the other one is based on real interaction information. The result showed that the above tendency is more common in community separation based on real interaction information. The present study will create a new path to evaluate communities detected in different community detection methods in terms of body motion synchrony.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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