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Wireless Networks and Mobile Communication - 1

2020· article· en· W4249011576 on OpenAlexafffund

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsTelecommunicationsComputer scienceWireless networkWired communicationWirelessMobile telephonyThe InternetPersonal Communications ServiceWorld Wide WebMobile radioWi-Fi array

Abstract

fetched live from OpenAlex

Welcome message from ChairsIt is our great pleasure to welcome you to the International Conference on Wireless Networks and Mobile Communications (WINCOM 2020), virtually from Reims, France.The WINCOM is a flagship conference of the MobiTic Association and represents one of the largest gatherings of researchers and industry professionals in the field of wireless communication networks and mobile communications in the world.In recent decades, wireless communication networks have fundamentally transformed our live.The technology itself is progressing and exploring new horizons.The delegates in WINCOM 2020 will discuss and present the latest advances in next generation networking in wireless networks and mobile communications.A diverse range of topics from fifth generation (5G) technology, Internet of Things (IoT), as well as energy efficiency and green communication systems are featured in the conference.However, the major transformation is likely due to the increased infiltration of communication capability in new application domains with large impact on many sectors of our economy, and the potential to lead to new paradigms in manufacturing, services and transportation.Organization of a conference would not be possible without the dedicated efforts of many people.The WINCOM 2020 is indebted to hundreds of volunteers who contributed to the various processes that make up the conference and it would not be possible for us to name all of them in this short message.In particular, the Technical Program Committee, led by our indefatigable TPC Chairs, completed a thorough peer-review process of papers to select a comprehensive and high-quality technical program for the conference.This program is augmented and complemented by a number of Keynote Sessions of high caliber, organized through the efforts of our Chairs.Finally, we would like to thank all our sponsors in particular University of Reims Champagne-Ardenne, France, Mobitic Association and IEEE Communication Society and all supporters for their contribution to the conference.It has been a great privilege for us to serve as the chairs of WINCOM 2020 and it is our hope that you find the conference stimulating, fulfilling and enjoyable.We thank you for your support of WINCOM and your attendance.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0380.023

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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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