A Review of 6G and Next-Generation Internet: Under Blockchain Web3 Economy
Bibliographic record
Abstract
The sixth generation (6G) wireless cellular networks are anticipated to include the most recent advancements in network infrastructure and new technological discoveries.In addition to exploring more spectrum at high-frequency bands, it will bring together cutting-edge technical trends like blockchain, artificial intelligence (AI), and connected robotics.6G and Next-Generation Internet: Under Blockchain Web3 Economy by Abdeljalil Beniiche explores the human-centeredness of blockchain and Web3 economy for the 6G era.Abdeljalil Beniiche received his PhD in telecommunications from the Institut National de la Recherche Scientifique (INRS), Montréal, Canada.His research focuses on 6G networks, Tactile Internet, blockchain, information security, behavioral economics, and Society 5.0.His research findings have been published in many prestigious journals, such as IEEE Network, IEEE Wireless Communications, IEEE Communications Magazine, and IEEE/OSA Journal of Optical Communications and Networking.He has served and continues to serve on the technical program committees and is a reviewer of numerous major international conferences, journals, and magazines.Currently, he is a Security Architect in the financial industry.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".