MétaCan
Menu
Back to cohort
Record W3128026765 · doi:10.1115/1.2164452

Modeling of Evolutionary Design Database

2005· article· en· W3128026765 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 Computing and Information Science in Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceConsistency (knowledge bases)AncestorDescendantDatabaseGenerative DesignDatabase designConceptual designArtificial intelligenceEngineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

This research introduces an evolutionary design database model to describe design requirements and design results developed at different design stages from conceptual design to detailed design. In this model, the evolutionary design database is represented by a sequence of worlds corresponding to the design descriptions at different design stages. The design requirements and design results in each world are modeled using a database representation scheme that integrates both geometric descriptions and nongeometric descriptions. In each world, only the differences with its ancestor world are recorded. When the design descriptions in one world are changed, these changes are then propagated to its descendant worlds automatically. Consistency of the design descriptions in descendant worlds is also checked when design descriptions in an ancestor world are changed. A case study is conducted to show the effectiveness of this evolutionary design database model.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.005
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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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