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Record W1984926386 · doi:10.1109/mele.2013.2272481

Courting and Sparking: Wooing Consumers? Interest in the EV Market

2013· article· en· W1984926386 on OpenAlex
Narayan C. Kar, K. Lakshmi Varaha Iyer, Anas Labak, Xiaomin Lu, Chunyan Lai, Aiswarya Balamurali, Bryan Esteban, M.A. Sid-Ahmed

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 Electrification Magazine · 2013
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAppealMarket penetrationMarketingAdvertisingQuality (philosophy)BusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

The concept of electrified vehicles (EVs) is the best old "new" idea that has been around for the last century. Designs have changed to make EVs popular, but until now, no design has captured the public's imagination or gained market traction. This is because consumers need more than facts about EVs; they need to be wooed into making a bigger commitment to the EV. The winning combination of making the EVs indispensable to the average North American consumer can be found in accessible charging infrastructures, reliable long-life batteries, and increased mileage. Vehicle manufacturers want a better-quality Ev to offer consumers to increase market penetration. Engineers and policy makers, to make this relationship a reality, need to appeal to more than just consumers' minds and go beyond testing and performance statistics and test results.

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: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.421

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 head0.209
Teacher spread0.194 · 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