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Necessity and limitations of transportation electrification

2024· article· en· W4396664877 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

VenueApplied and Computational Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsElectrificationPrioritizationEnergy securityRisk analysis (engineering)Rural electrificationEnvironmental economicsBusinessComputer scienceEconomicsElectricityEngineeringManagement scienceRenewable energy

Abstract

fetched live from OpenAlex

In recent times, there has been a significant surge in the prioritization of electrifying the transportation sector. The heightened focus on these factors might perhaps be attributed to the industry’s ability to effectively tackle and mitigate environmental problems and handle energy security challenges. This research examines the fundamental variables that are propelling the shift towards electrification within the transportation industry, alongside the limitations and obstacles linked to the extensive implementation of this technological advancement. As the transportation electrification business continues to expand, several doubts, such as spontaneous combustion, have led many to question the appropriateness of its further development. Gaining a thorough comprehension of the electrification trend and its possible constraints via an analysis of technological, economic, and infrastructural aspects proves to be very advantageous. In addition, understanding the fundamental reasons for the limitations of transportation electrification can help develop new technologies to enhance its electrification level in the future.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.646
Threshold uncertainty score0.255

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 head0.015
GPT teacher head0.221
Teacher spread0.207 · 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