Gigabit American advanced networks: emulation of the 2024 backbone topology under IPv6
Bibliographic record
Abstract
Time in time, Internet Service Providers around the world make updates in backbone topology and infrastructure, it includes de commercial Internet and the Internet 2, also known as advanced networks or national research and education networks. Previous works offered the connectivity and management emulation of the backbone network for CANARIE, INTERNET2 and CLARA, the three advanced networks in America for Canada, USA and Latin American under IPv4 for the 2019 topology. In this the work some updates are offered, this way it is considered the connectivity and management emulation for the four backbone networks under IPv6 for the updated topology up to 2024 and updates for BGP-4 for Autonomous Systems in 2024, also is indicated the use of virtual machines and IReasoning MIB Browser software for the network management. When integrating the three topologies, the backbone network resulting covers 13 countries in the continent. The resulting emulations review the management assessment and topology show how some topologies are evolving in case of CANARIE and INTERNET2, but CLARA is having some difficult to maintain the same countries connected, some of the decisions are taken based on the use and development of strategic projects. These results could be useful for next upgrades and the grow of the advanced networks in the continent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".