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Record W4233570619 · doi:10.1145/1641913

Proceedings of the 4th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks

2009· paratext· en· W4233570619 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)Computer scienceWirelessWireless networkTelecommunicationsWireless sensor networkLibrary scienceOperations researchEngineeringComputer network

Abstract

fetched live from OpenAlex

We are pleased to welcome you to the Fourth ACM International Workshop on Performance Monitoring, Measurement, and Evaluation of Heterogeneous Wireless and Wired Networks (PM2HW2N'09), held this year in conjunction with the 12th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2009), on October 26-30, 2009 in Tenerife, Canary Islands (Spain). Following the success of the former three editions, which were held in Torremolinos (Málaga, Spain, 2006), in Chania (Crete Island, Greece, 2007), and in Vancouver (Canada, 2008), PM2HW2N'09 aims at providing researchers from both academia and industry with a forum to share and exchange their experiences, discuss challenges, and report state-of-the-art and in-progress research on all aspects of monitoring and measurement of heterogeneous wireless and wired networks with a specific emphasis on performance modeling, evaluation and analysis. In response to our call for papers, we have received a large number of papers related to the above research issues. All of the papers submitted have been peer-reviewed by at least two referees from the Technical Program Committee, with most of the papers being reviewed by three referees. Based on the outcome of the reviews, a good set of top papers has been selected for publication in this ACM proceedings and for presentation at the workshop as full papers.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.033
GPT teacher head0.255
Teacher spread0.221 · 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.

Study designOther design
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

Citations4
Published2009
Admission routes1
Has abstractyes

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