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Record W2051736072 · doi:10.1243/09596518jsce231

Integrated design of function, usability, and aesthetics for automobile interiors: State of the art, challenges, and solutions

2006· article· en· W2051736072 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

VenueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · 2006
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUsabilityRelevance (law)Function (biology)Set (abstract data type)Product (mathematics)Computer scienceProduct designSubject (documents)Focus (optics)Process (computing)Architectural engineeringAestheticsHuman–computer interactionEngineeringMathematicsWorld Wide WebArt

Abstract

fetched live from OpenAlex

This paper presents a critical review of aesthetic design with a focus on the application of vehicle interiors. In particular, the following aspects of the subject are covered: first, aesthetics and its relevance to product design; second, the integrated aesthetic design process; third, the evaluation of aesthetic responses; fourth, the notion of intelligent vehicle interiors; fifth, the computational methods for aesthetic design. Shortcomings in existing studies related to vehicle aesthetic design are identified and analysed. The methodology employed to conduct this review is such that a set of questions important to these aspects are defined first, and then existing studies are analysed on the basis of their provision of answers to these questions. At the end, several ideas are proposed, which are brought together as a software environment, with the goals of overcoming these identified shortcomings and advancing the automobile interior aesthetic design technology.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.226
Teacher spread0.201 · 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