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Record W2036906995 · doi:10.1109/bmsb.2013.6621714

Cloud Transmission: System simulation and performance analysis

2013· article· en· W2036906995 on OpenAlexaff
Jon Montalbán, Bo Rong, Sung-Ik Park, Yiyan Wu, Jeongchang Kim, Heung Mook Kim, Liang Zhang, Charles E. Nadeau, Sebastien Lafleche, Pablo Angueira, Manuel Vélez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsComputer scienceCloud computingRobustness (evolution)Broadcasting (networking)Multipath propagationTransmission (telecommunications)Multipath interferenceComputer networkSingle-frequency networkInterference (communication)TelecommunicationsTransmission systemChannel (broadcasting)Electronic engineeringEngineeringOperating system

Abstract

fetched live from OpenAlex

The Cloud Transmission (Cloud Txn) is a new paradigm of broadcasting or point-to-multipoint transmission system, designed for efficient and flexible use of the spectrum, robustness against noise, multipath and co-channel interference, and capability to provide fixed or mobile reception while using low transmission power. Besides system capability, the system should meet many other challenging issues. The main purpose of this work is to demonstrate that this proposed new system is feasible and it meets today and future needs of the broadcasting industry.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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 designSimulation or modeling
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

Citations12
Published2013
Admission routes1
Has abstractyes

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