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Record W4413737679 · doi:10.1017/pds.2025.10014

A community-driven database for the dynamic representation of approaches, processes, methods, and tools for multidisciplinary product development

2025· article· en· W4413737679 on OpenAlex
Benoît Eynard, Julia Guérineau

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings of the Design Society · 2025
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsÉcole de Technologie Supérieure
FundersMitacs
KeywordsMultidisciplinary approachRepresentation (politics)Computer scienceDevelopment (topology)New product developmentProduct (mathematics)DatabaseProcess managementManagement scienceIndustrial engineeringSystems engineeringData scienceEngineeringSociologyMathematicsBusinessPolitical scienceSocial science

Abstract

fetched live from OpenAlex

ABSTRACT: The advent of multidisciplinary product development may require a corresponding evolution or adaptation of product development practices within companies. To support this, researchers have developed various groupings of concepts and techniques, such as “toolboxes” or “maps”, which can be assimilated to static databases. Consequently, this article presents a first step towards a community-driven database for the dynamic representation of links between approaches, processes, methods and tools in research documents. Following a comparative analysis of different representations, a preliminary design of a dynamic database is presented using Unified Modeling Language models to define its architecture. A use case diagram paired with screenshots of the dynamic database presents the core functionalities, which include real-time data filtering, visualisation, navigation and modification.

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)0.002
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.256
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.154
GPT teacher head0.378
Teacher spread0.223 · 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