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Record W2314018711

Wireless future: green and cooperative networking?

2009· article· en· W2314018711 on OpenAlexaff
Maria Luisa Merani, Vijay K. Bhargava, Flavio Boano, Giridhar Mandyam, Roberto Saracco, P. Stuckmann, Reinaldo A. Valenzuela

Bibliographic record

VenueInternational Symposium on Wireless Communication Systems · 2009
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsViewpointsWirelessComputer scienceWireless networkEuropean commissionComputer networkTelecommunicationsBusinessEuropean union
DOInot available

Abstract

fetched live from OpenAlex

The cooperative principle is expected to be effective in having wireless users more satisfyingly achiev their communication goals. Different layers are anticipated to benefit from its strength, from the low physical and network lev els, up to the service level, where novel, exciting applications such as IP-TV are rousing. This trend is paralleled by an increased consciousness that wireless devices(from end-user handsets to wireless routers) have to be designed paying a specific attention to environmental efficiency: again, this translates into smart power management solutiions at RF level, but also in skillful algorithm design, carefully tailored communication protocols, lightweight and distributed databases. The incited experts will provide the audience with sharp, brief presentations reflecting their ideas on such topics, and will interact answering the questions raised by the floor. A specific attention will be devoted to the industy and European Commission viewpoints on the subjects the panel is centered upon.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0050.015
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.248
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations0
Published2009
Admission routes1
Has abstractyes

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