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Record W4236460812 · doi:10.1109/lcomm.2019.2928735

IEEE Communications Society

2019· article· en· W4236460812 on OpenAlexfundno aff

Bibliographic record

VenueIEEE Communications Letters · 2019
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Optimization
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversity of West AtticaUniversité Paris 13Université Paris-Est Créteil Val-de-MarneInstitut National des Sciences Appliquées de LyonShenzhen UniversityUniversity of Science and Technology BeijingTarbiat Modares UniversityUniversidad Carlos III de MadridUniversity of AkronSouth China University of TechnologyUniversité de Bretagne OccidentaleTsinghua UniversityScuola Superiore Sant'AnnaKing Fahd University of Petroleum and MineralsUniversidade de CoimbraKing's College LondonDeutsches Zentrum für Luft- und RaumfahrtIstanbul Teknik ÜniversitesiChalmers Tekniska HögskolaBeijing University of Posts and TelecommunicationsSun Yat-sen UniversityHanyang UniversitySoutheast UniversityIndian Institute of Technology, PatnaUlster UniversityUtah State UniversityUniversity of the West of ScotlandLoughborough UniversityUniversity of AlbertaUniversidad de MálagaYork UniversityNorthumbria UniversityUniversity of OttawaTrường Đại học Bách Khoa Hà NộiIndian National Science AcademyTrường Đại học Duy TânUniversity of Electronic Science and Technology of ChinaSoongsil UniversityNational University of SingaporeUniversità degli Studi di Napoli ParthenopeUniversità di BolognaOld Dominion UniversityUniversité de BordeauxChinese University of Hong KongUniversità degli Studi di Napoli Federico IIUniversity of British ColumbiaVillanova UniversityQatar UniversityIndian Institute of Technology DelhiUniversity of Ontario Institute of TechnologyQueen Mary University of LondonKing Abdullah University of Science and TechnologyPohang University of Science and TechnologyUniversity of South AlabamaUniversity of Science and Technology of ChinaBeijing Jiaotong UniversityNational Sun Yat-sen UniversityIndian Institute of Technology IndoreSanta Clara UniversityDeakin UniversityUniversity of MacedoniaHeriot-Watt University
KeywordsComputer scienceTelecommunicationsComputer network

Abstract

fetched live from OpenAlex

IEEE COMMUNICATIONS LETTERS is aimed at satisfying the need for rapid dissemination of information, offering a vehicle for authors to expose their results to be used in future developments. This ensures early recognition of work. The objective is to establish a highly authoritative outlet for new results in communications world wide, presenting archival material and bestowing prestige on the authors as a result of IEEE Communications Society's high standards for publication. Emphasis is on the use of advanced communication tools such as fax machines, electronic mail, and other electronic media (including the possibility of printing directly from electronic copy). The anticipated time of three months from submission to publication would depend on the method of communication of information, in association with relatively straightforward, though stringent, review procedures; requiring referee responses within four weeks. All members of the IEEE are eligible for membership in the society upon payment of the annual society membership fee of $33.00.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.235
Threshold uncertainty score0.787

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2350.262

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 head0.288
Teacher spread0.255 · 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
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".

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Citations0
Published2019
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