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Record W4233551028 · doi:10.1109/mmm.2014.2362593

RWW Advance Program

2014· article· en· W4233551028 on OpenAlexaff

Bibliographic record

VenueIEEE Microwave Magazine · 2014
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceEngineering

Abstract

fetched live from OpenAlex

The millimeter-wave frequency band is seen as a good candidate for future 5G mobile radio networks. The availability of multiple Gigahertz of bandwidth promises to be an answer to the ever increasing data rates in access and backhaul links. At the same time new challenges arise. Mass production of RF communication circuits for this band is at its beginning. The knowledge on the outdoor channel is still very limited. New approaches for integrated steerable high gain antennas are necessary to counter the higher path loss at the high frequencies. The network architecture is expected to become more and more heterogeneous with a mixture of different cell radii and the wide deployment of small cells. With views from industrial and scientific research this workshop will give an overview on the state of the art and the huge potentials of millimeter-waves in 5G.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.630
Threshold uncertainty score0.527

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6300.554

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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.

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
Published2014
Admission routes1
Has abstractyes

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