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Record W33837419 · doi:10.1093/jnen/nlab033

Proceedings of the ACM SIGCOMM workshop on Future directions in network architecture

2004· article· en· W33837419 on OpenAlexaff
Kevin Fall, Srinivasan Keshav

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceTroubleshootingArchitectureOutreachIncentiveSet (abstract data type)Game theoryWorld Wide WebOperations researchTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

It is a great pleasure to welcome you all to the ACM SIGCOMM 2004 Workshops!We are pleased to present an outstanding program consisting of four workshops: (1) Future Directions in Network Architecture (FDNA); (2) Network and System Support for Games (NetGames); (3) Practice and Theory of Incentives in Networked Systems (PINS); and (4) Network Troubleshooting: Research, Theory, and Operations Practice Meet Malfunctioning Reality (NetTs).Workshops were first introduced as a part of the ACM SIGCOMM week-long Data Communications Festival in 2003 to enhance the ACM SIGCOMM conference technical program; this is the second year for this effort. In response to the call for proposals, we received 6 workshop proposals, 4 of which were accepted. FDNA, the highly successful workshop from 2003, is repeated for the second year. This is the first year for NetGames, PINS, and NetTs; a key feature of all of these workshops is their outreach to other communities. NetGames -- organized for the first time in conjunction with the ACM SIGCOMM conference -- brings together multimedia and gaming community with networking; PINS (organized in collaboration with ACM SIGecom) crosses the boundaries between economics, game theory, and networking; and NetTs exposes challenges in network operations to networking researchers.Organizing such a diverse set of workshops requires a great deal of effort and organization and I want to thank all the members of the SIGCOMM 2004 organizing committee and several volunteers who made it possible. I would like to thank Craig Partridge, Jennifer Rexford, John Wroclawski, and Jim Kurose for their suggestions and help in soliciting exciting workshop proposals. I also thank the SIGCOMM 2004 organizing committee, and in particular, Raj Yavatkar, Jennifer Rexford, Chris Edmondson-Yurkanan and Joe Touch for all the support and guidance they provided throughout the workshop organization process. The local arrangements for the workshops are a result of efforts of Wu-chang Feng. Prashant Chandra, Andreas Terzis, Marcel Waldvogel, and Allyn Romanow handled the web pages, registration, and publicity for the workshops.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0080.013
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0510.012

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2004
Admission routes1
Has abstractyes

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