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Record W2982634520 · doi:10.1109/mce.2019.2941467

Cellular V2X Transmission for Connected and Autonomous Vehicles Standardization, Applications, and Enabling Technologies

2019· article· en· W2982634520 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Consumer Electronics Magazine · 2019
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsCarleton UniversityQueen's University
Fundersnot available
KeywordsStandardizationComputer scienceKey (lock)Low latency (capital markets)Transmission (telecommunications)TelecommunicationsComputer networkSystems engineeringComputer securityEngineering

Abstract

fetched live from OpenAlex

Connected and autonomous vehicles (AVs) will need to communicate significant amounts of data to provide various safety, navigation and infotainment services to consumers. This article discusses the recent technological advances and standardization efforts in Cellular Vehicle-to-Everything (C-V2X) technologies that are being developed to support the ultra-reliable, low latency, and high throughput required by AVs. The key V2X applications and their communication requirements, with an emphasis on video delivery, are then presented. In conclusion, we highlight the primary challenges of V2X network design, and present several future research directions including the role of network intelligence to facilitate large-scale deployments of V2X applications.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.586
Threshold uncertainty score0.942

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.196
Teacher spread0.191 · 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