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Record W4404797459 · doi:10.1080/09544828.2024.2432835

Computer-aided design as a research instrument for engineering design: supporting multiple methods by observing artifacts, actors, and actions

2024· article· en· W4404797459 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

VenueJournal of Engineering Design · 2024
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSystems engineeringHuman–computer interactionComputer scienceEngineeringDesign methodsEngineering drawingSoftware engineeringManagement scienceEngineering managementMechanical engineering

Abstract

fetched live from OpenAlex

Scholars studying engineering design have long identified three essential, interacting elements: the artifact being designed, the actors designing it, and the actions they take to do so. However, concerns about tractability and the effort required to capture data on all three have often led to studies examining only one or two at a time, potentially obscuring important (and explanatory) dynamics. Addressing this gap, Computer-Aided Design (CAD) platforms can observe all three elements simultaneously, unobtrusively, over the entire duration of the design process, and across many different contexts. Whether the research is inductive, abductive, or deductive, these platforms can improve a study’s internal, external, construct, and face validity if wielded wisely. As such, we advocate CAD as the central research instrument to study micro-level engineering design.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.210
GPT teacher head0.417
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