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Record W4245460010 · doi:10.1145/1868497

Proceedings of the 8th ACM international workshop on Mobility management and wireless access

2010· paratext· en· W4245460010 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsnot available
Fundersnot available
KeywordsGlobePresentation (obstetrics)Computer scienceTelecommunicationsMobility managementWireless networkWirelessLibrary scienceMedicine

Abstract

fetched live from OpenAlex

It is our great pleasure to welcome you to the 8th ACM International Symposium on Mobility Management and Wireless Access -- MobiWac '10 in Bodrum, Turkey. Following the successful previous events in Fort Worth (TX), Philadelphia (PA), Maui (Hawaii), Torremolinos (Spain), Chania (Greece), Vancouver (Canada) and Tenerife (Spain), this year's symposium continues the tradition of being a premier forum for presentation of research results and experience reports on leading edge issues of mobility and wireless access, including models, systems, applications, and theory. The mission of the symposium is to share novel mobility management and wireless network solutions and identify new directions for future research and development. MobiWac gives researchers and practitioners a unique opportunity to share their perspectives with others interested inthe various aspects of Mobile and Wireless Systems. The call for papers attracted 36 submissions from around the globe. The program committee accepted 14 regular papers, which represents an acceptance rate of 39%. These papers cover a variety of topics, including next generation access control models, engineering and analysis techniques for access control policies and models, and resource management. The program committee further accepted 4 papers as short papers. All submissions were fully peer reviewed. We hope that these proceedings will serve as a valuable reference for mobile and wireless systems researchers and developers.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 designNot applicable
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

Citations1
Published2010
Admission routes1
Has abstractyes

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