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Record W2965468646 · doi:10.1017/dsi.2019.144

An Exploratory Study Comparing CAD Tools and Working Styles for Implementing Design Changes

2019· article· en· W2965468646 on OpenAlex
Vrushank Phadnis, Kevin Leonardo, David R. Wallace, Alison Olechowski

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 ... International Conference on Engineering Design · 2019
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCADComputer scienceDependency (UML)ProductivityTree (set theory)Value (mathematics)Collaborative designExploratory researchHuman–computer interactionEngineering drawingSoftware engineeringMachine learningEngineeringSystems designMathematics

Abstract

fetched live from OpenAlex

Abstract This paper presents the findings of a preliminary study comparing implementation of design changes using various computer-aided design (CAD) working styles. Our study compares individuals’ and pairs’ completion of a series of changes to a toy car CAD model. We discuss the results in terms of productivity and value added ratio, derived from time-based quantitative data. We also discuss qualitative findings acquired through post-study surveys. Overall, our findings suggest that pairs were less efficient than individual designers due to overheads like communication, history dependency and complex couplings within the CAD model tree. However, it is also noteworthy that within each pair the lead participant's performance was at par with individual participants. Lastly, we also discuss behaviors and patterns that emerge as unique to the synchronous collaborative environment, motivating future work.

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: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.706

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 head0.150
GPT teacher head0.304
Teacher spread0.154 · 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