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Record W4409671774 · doi:10.1049/icp.2025.1260

Gigabit American advanced networks: emulation of the 2024 backbone topology under IPv6

2025· article· en· W4409671774 on OpenAlexaboutno aff
Jorge Hernández Castillo, Nelly-Guadalupe Velazquez-Cruz

Bibliographic record

VenueIET conference proceedings. · 2025
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsnot available
Fundersnot available
KeywordsGigabitEmulationIPv6Computer networkComputer scienceNetwork topologyTopology (electrical circuits)TelecommunicationsElectrical engineeringOperating systemEngineeringThe InternetPsychology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.250
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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