MétaCan
Menu
Back to cohort
Record W4304607358 · doi:10.1155/2022/3868388

A Comprehensive Review on the Integration of Electric Vehicles for Sustainable Development

2022· review· en· W4304607358 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Advanced Transportation · 2022
Typereview
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentElectric vehicleRisk analysis (engineering)BusinessSustainable transportEnvironmental economicsTransport engineeringIndustrial organizationComputer scienceSustainabilityEngineeringEconomicsPolitical science

Abstract

fetched live from OpenAlex

In this article, the concept of an electric vehicle (EV) as a sustainable development (SD) is discussed, and the viability of the development of electric vehicles is assessed. This study broadens the conventional definition of sustainable development by incorporating and prioritizing crucial areas of technology, environment, and policy performance. The proposed review studies have summarized the elements that can promote the integration of electric vehicle technology. The innovation of the EV has just become a modern innovation. At the same time, some obstacles, such as policy and lower adoption, are resisting its goals. To overcome this situation, electric cars have to adopt some innovative approaches that can be another path to success. The review result shows that the proposal discusses the technological advancements of electric vehicles worldwide and paves the way for further improvements. The results also mentioned technological development to reduce emissions and help us understand the impact on the environment and health benefits. However, the summary would be advantageous to both scholars and policymakers, as there is a lack of integrative reviews that assess the global demand and development of EVs simultaneously and collectively. This review would provide insight for investors and policymakers to envisage electric mobility.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.275
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