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Record W4245707316 · doi:10.1109/glocomw.2012.6477510

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2012· article· en· W4245707316 on OpenAlexaff
Alberto Leon‐Garcia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsNatural Sciences and Engineering Research CouncilUniversity of Toronto
Fundersnot available
KeywordsTestbedComputer scienceCloud computingVirtualizationOpenFlowThe InternetEdge computingComputer networkTelecommunicationsWorld Wide WebSoftware-defined networkingOperating system

Abstract

fetched live from OpenAlex

In this talk we consider application platforms for enabling applications and services over a converged computing and communications infrastructure. We consider future programmable application platforms where users and providers of content, services and infrastructure interact in an open applications marketplace that is in the center of social and economic activity. We consider an extended computing cloud that includes massive-scale core datacenters, the Internet, a "Smart Edge", and a converged wireless/optical access. We investigate an approach where all resources are managed using virtualization and adaptive management principles. In particular we explore the design of the smart edge and its role in the dynamic management of a virtualized access network. We describe associated testbed development activities of the NSERC Strategic Network on Smart Applications and Virtual Infrastructures, and we discuss how we are leveraging the OpenStack and OpenFlow open source activities.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.256
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0060.004
Open science0.0020.006
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.7440.537

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 head0.020
GPT teacher head0.235
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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