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Record W4411307952 · doi:10.21606/drs.2010.127

Interdisciplinary Design: The Need for Collaboration to Foster Technological Innovation to Create Competitive and Sustainable Products.

2010· article· en· W4411307952 on OpenAlexaff
Peter Wehrspann, Lois Frankel

Bibliographic record

VenueProceedings of DRS · 2010
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsInnovation managementKnowledge managementBusinessCompetitive advantageComputer scienceProcess managementMarketing

Abstract

fetched live from OpenAlex

This paper explores an integral relationship between industrial design, advanced technologies, science, economy, and the environment to realize a logical trajectory for the future of product design. Through an investigation of current literature, key aspects and critical factors of interdisciplinary collaborative work are explored. By realizing the benefits and obstacles, this paper suggests a framework in which scientists, engineers, and designers can work together successfully to create innovative solutions for product design. The paper discusses the possibilities of material synthesis through the scientific field of biomimetics. It also suggests that the Industrial designer’s role must evolve into a position of project facilitator and communicator. To conclude, this paper mentions technologies utilized currently in this fashion and ideas are proposed to further guide this framework.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.013
Scholarly communication0.0120.011
Open science0.0020.014
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.017
GPT teacher head0.285
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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