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Record W64125330

Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing

2010· article· en· W64125330 on OpenAlexaboutno aff
Nitin H. Vaidya, Christoph Lindemann, Jitendra Padhye

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceWireless ad hoc networkEleventhVariety (cybernetics)TelecommunicationsLibrary scienceWorld Wide WebWirelessArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Welcome to ACM MobiHoc 2010, the 11th ACM International Symposium on Mobile Ad Hoc Networking and Computing! ACM MobiHoc is the premier international symposium dedicated to addressing challenges emerging from wireless ad hoc networking and computing. The mission of the symposium is to bring together researchers and practitioners from a broad spectrum of wireless networking research to present the most up-to-date results and achievements in the field. As in previous years, the paper selection process was highly competitive. The call for papers attracted 157 submissions from Asia, Canada, Europe, and the United States. All papers were reviewed through a double blind review process. Each paper was reviewed by at least three program committee members not connected with the authors; most papers received four reviews and for some papers even five reviews were written. After the online-discussion phase, the top 57 papers were selected to be discussed in detail at the TPC meeting. The TPC meeting took place at Microsoft Research in Redmond on May 27 and 28, 2010 and 26 papers were selected for inclusion in the technical program. The technical program covers a variety of topics, including mobility, modeling and analysis, routing and forwarding, scheduling, security, sensor networking, and spectrum allocation. Wehope that these proceedings will serve as a valuable reference for mobile networking researchers and practitioners. We hope that you will find this program interesting and thought-provoking and that the symposium will provide you with a valuable opportunity to share ideas with other researchers and practitioners from institutions around the world.

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 score0.867
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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