Bibliographic record
Abstract
네트워크 장비 업체나 통신사뿐만 아니라 여러 국가들에서도 상용화를 목표로 5G 기술 확보를 위한 대규모의 연구 개발 역량을 집결하고 있다. 이 중 대다수의 연구 개발은 SDN(Software Defined Network)과 NFV(Network Function Virtualization)를 기반으로 두고 있다. 이는 5G의 아키텍처가 동적인 네트워크를 생성하는데 초점을 맞추고 있기 때문이다. 이에 본 고에서는 METIS 2020(Mobile and wireless communication Enablers for the Twenty-twenty Information Society)에서 발표한 최종 리포트를 참고하여 5G 이동통신 네트워크에서의 SDN과 NFV의 역할에 대해 알아 보고, 현재 진행 중인 개발 행태를 보기 위해 대표 기업들의 동향을 살펴본다.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".