IEEE Access Special Section Editorial: Trust Management in Pervasive Social Networking (TruPSN)
Bibliographic record
Abstract
With the rapid growth of mobile computing and social networking, social networks have extended their popularity from the Internet to mobile domain. Pervasive Social Networking (PSN) ensures social communications at any time and in any place with a universal manner. It supports online and instant (i.e., pervasive) social activities based on heterogeneous networks, e.g., the Internet, mobile cellular networks or self-organized networks or other networking technologies. It is treated as one of the killer applications in the next generation mobile networks and wireless systems (i.e., 5G). There are various applications over PSN. Typical examples include social chatting, gaming, rescuing, recommending and information sharing. Because group mobility is very common in modern life, PSN has become valuable for mobile users, especially when they are familiar strangers and often appear in the same vicinity. PSN greatly extends our experiences of social communications.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".