MétaCan
Menu
Back to cohort
Record W1959038507 · doi:10.24908/pceea.v0i0.3862

THE USE OF PRODUCT DATA MANAGEMENT (PDM) SOFTWARE TO SUPPORT STUDENT DESIGN PROJECTS

2011· article· en· W1959038507 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsProduct data managementVariety (cybernetics)Product (mathematics)Data managementSoftware engineeringData sharingSoftwareComputer scienceEngineering managementSystems engineeringNew product developmentEngineeringProduct lifecycleDatabaseOperating systemBusiness

Abstract

fetched live from OpenAlex

Industry recognizes the central importance of managing and sharing CAD data within the organization, and powerful Product Data Management (PDM) systems have been developed to address this need However, engineering schools have been slow to adopt PDM technology, and student design teams typically rely on a variety of ad hoc approaches to manage shared CAD data. To address the PDM requirements of student projects, the University of Western Ontario acquired and deployed PDMWorks in January 2006. PDMWorks is a midrange PDM system for SolidWorks. Installation and administration of this midrange product are very straightforward, and its tight integration with SolidWorks makes PDMWorks easy to use. However, PDMWorks is best suited to relatively small workgroups, and does not scale easily to large numbers of users.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.058
GPT teacher head0.229
Teacher spread0.170 · 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