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Record W2593484648 · doi:10.1109/mcom.2016.7470938

LTE-advanced pro: part 1 [Guest Editorial]

2016· article· en· W2593484648 on OpenAlexaff
Robert W. Heath, Michael L. Honig, Satoshi Nagata, Stefan Parkvall, Anthony C. K. Soong

Bibliographic record

VenueIEEE Communications Magazine · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsScience North
Fundersnot available
KeywordsComputer scienceTelecommunicationsMobile broadbandWirelessPenetration rateIMT AdvancedBroadbandMobile telephonyTerm (time)LTE AdvancedMobile computingMobile technologyComputer networkMultimediaMobile WebMobile radioTelecommunications linkEngineering

Abstract

fetched live from OpenAlex

Long Term Evolution (LTE) has become the most successful mobile wireless broadband technology, serving over one billion users as of the beginning of 2016. However, looking at the penetration rate, LTE serves only 14.5 percent of the current 7.3 billion mobile subscriptions. Consequently, there is still significant room for LTE to grow as a mobile technology; it will be serving users for a long time to come.

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 categoriesInsufficient 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 score0.796
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.264
Teacher spread0.242 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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