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Record W64489891

Proceedings of the 2nd ACM SIGCOMM workshop on Green networking

2011· article· en· W64489891 on OpenAlexaff
Shivkumar Kalyanaraman, Catherine Rosenberg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScope (computer science)Computer scienceNexus (standard)TelecommunicationsPanel discussionBusiness
DOInot available

Abstract

fetched live from OpenAlex

Welcome to the Second ACM SIGCOMM Workshop on Networking! The energy consumption and environmental impact of networking and communications equipment is of increasing importance to researchers, commercial entities and society at large. The Second ACM SIGCOMM Workshop on Networking aims to continue the exciting first edition of the workshop, to create a dynamic forum for discussing green networking issues. This year we have expanded the scope of the workshop to also present promising research ideas at the nexus of energy and IT domains and in the field of smarter energy systems. This year's call for papers attracted 19 submissions on a diverse set of topics ranging from energy harvesting to data center cooling to characterization of smarter homes to photonic coding. The 14 member Technical Program Committee along with a selected group of external experts carefully considered all of the submissions. The committee had assembled a program composed of 8 papers that will be presented during the workshop. The workshop will also feature a keynote talk on Smart Grids and a panel Green Networking: Tip of the Iceberg or The Polar Bear? featuring leading academia and industry participants.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.543

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 science0.0030.001
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 head0.045
GPT teacher head0.222
Teacher spread0.177 · 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 designSimulation or modeling
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

Citations11
Published2011
Admission routes1
Has abstractyes

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