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Vehicular Networks for a Greener Environment: A Survey

2012· article· en· W2161298857 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 Communications Surveys & Tutorials · 2012
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceImplementationWireless ad hoc networkOpen researchPower consumptionVehicular ad hoc networkFuel efficiencyTelecommunicationsVehicular communication systemsPerspective (graphical)Computer securityComputer networkWirelessPower (physics)World Wide WebEngineeringSoftware engineering

Abstract

fetched live from OpenAlex

Researchers are looking for solutions that save the environment and money. Vehicular ad-hoc networks (VANETs) offer promising technology for safety communications. Thus, researchers try to integrate certain applications into existing research. The current survey critically examines the use of vehicular communication networks to provide green solutions. We discuss the current implementations of technology and provide a comparison from the communication perspective. This paper is meant to motivate researchers to investigate a new direction in which a network of vehicles is used to enhance total fuel and power consumption, gas emissions, and-as a result-budgets. Moreover, open issues and research directions that have only been slightly addressed, if at all, are discussed.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.049
GPT teacher head0.265
Teacher spread0.216 · 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