Bibliographic record
Abstract
We warmly welcome you to Istanbul, Türkiye and to the 16th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN-2025). With the help and support of the technical committees we have put together an exciting technical program for this years’ EUSPN conference. We hope you enjoy the program and have fruitful interactions and discussions with researchers and practitioners gathering here from around the world. EUSPN is a leading international conference for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all Ubiquitous Systems and Pervasive Networks related areas. EUSPN 2025 is held in Istanbul, Türkiye, October 28-30. In addition to the keynote and technical sessions, we have workshops dealing with more specific aspects on EUSPN topics accompanied the main conference. These workshops had their own organizing committees and refereeing process. EUSPN 2025 received 132 papers from the authors representing many continents and countries. The papers were submitted to different tracks wherein each track has a separate technical program committee. Each submitted paper was reviewed by 2 to 4 domain experts in their respective tracks. Based on these reviews, we accepted 43 papers making an acceptance rate of 32.57%. It is our wish and hope that the people participating in the conference will find common ground on which they can learn from each other, and that the conference engenders future fruitful scientific activities. We wish to thank the General Chairs, the Advisory Committee, the Workshops’ Chair, the Organizers of the Workshops, the Local Arrangements Chairs, the Publicity Chairs, the Technical Program Committee of all tracks, the participants, and, most importantly, the researchers who submitted the articles which appear here. We look forward to hearing productive and interesting discussions during the EUSPN 2025 conference. We wish you a pleasant stay and an enjoyable time in Istanbul, Türkiye!
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.452 | 0.326 |
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".