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Record W2052424261 · doi:10.1504/ijhvs.2012.045762

RETRACTED ARTICLE An alternative approach to CB radio using point-to-point communications

2012· article· en· W2052424261 on OpenAlexaff
Yasser Morgan, Thomas Kunz, S. Seenappa

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueInternational Journal of Heavy Vehicle Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsCarleton UniversityUniversity of Regina
Fundersnot available
KeywordsDedicated short-range communicationsDefault gatewayQuality of servicePoint (geometry)Computer networkTelecommunicationsCommunications systemService (business)Point-to-pointEngineeringComputer scienceGateway (web page)WirelessWorld Wide Web

Abstract

fetched live from OpenAlex

In this paper we experiment with the modern point-to-point communication approach and redesign it to fulfil the classical application of serving Citizen Band (CB) radio. We provide a novel approach that utilises the modern Dedicated Short-Range Communications (DSRC) as highlighted for vehicular communications. Our approach involves establishing higher quality service for CB streaming traffic. We provide a system to use the heavy vehicle as a gateway for streaming traffic. We utilise the SWAN approach then we improve it by implementing a destination-based approach for real-time traffic regulation. We compare the destination-based regulation with the network-based regulation. We evaluate the impact of applying the enhanced SWAN model by testing the performance of both real-time and best-effort traffic. Finally, we comment on how the real-time streaming traffic service was enhanced without measurable impact on the best-effort services.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.996
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0530.024

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 head0.036
GPT teacher head0.290
Teacher spread0.254 · 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
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

Citations0
Published2012
Admission routes1
Has abstractyes

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