Satcom Convergence in the IP Multimedia Subsystem (IMS)
Bibliographic record
Abstract
The role of satellite telecommunications systems in the Next Generation Networks (NGN) has so far been peripheral. Satellites have been used for years for broadcasting, multicasting and content contribution in the radio and television world. They have been used for IP connectivity to large under-serviced areas. They have been used for mobile communications with systems such as Inmarsat. However, most satellite networks have been stand-alone and have not seen a tight integration with the terrestrial fixed and mobile network operators. The European Space Agency is supporting research and development in space telecommunications within its Advanced Research in Telecommunications Systems (ARTES) programme in order to help European and Canadian industry in their efforts to maintain competitiveness on the world market. In the area of satellite telecommunications systems and ground segment, several activities have been devoted to the development of new-generation two-way satellite IP-access networks for the provision of Internet services. A strategic element of our activities is to ensure that satellite networks and components can be seamlessly integrated in commercial terrestrial telecommunications networks. With this purpose in mind, the Agency has issued tenders to investigate the role of satellite in the context of the IP convergence process and the IP Multimedia Subystem (IMS). The objective of these projects is to demonstrate that satcom broadband systems can be seamlessly integrated within an IMS network, with compatible protocols and performance allowing the support of advanced multimedia applications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".