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Record W2111537628 · doi:10.1109/pacrim.1991.160755

An intelligent basis for design

2002· article· en· W2111537628 on OpenAlexafffund
Thomas Calvert, John Dickinson, John C. Dill, W.S. Havens, J. D. Jones, Lyn Bartram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicConstraint Satisfaction and Optimization
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCADComputer scienceExpert systemBacktrackingConstraint (computer-aided design)Knowledge baseProcess (computing)Dependency (UML)Software engineeringObject (grammar)Human–computer interactionComputer Aided DesignSystems engineeringEngineering drawingArtificial intelligenceEngineeringProgramming languageOperating system

Abstract

fetched live from OpenAlex

A description is presented of the first steps towards an intelligent CAD system based on a mixed-initiative approach. The expert system is an object-oriented model-based reasoning engine using constraint propagation and dependency backtracking. The architecture is built around the expert system, a CAD engine, and a user interface/controller module mediating the mixed-initiative relationship between designer and system. Initial experience has shown the need to model both experts and objects in the knowledge base and both the need and difficulty of representing design and constraint spaces to the designer. The preliminary results of a study of how people use a CAD system to better understand the design process itself suggest directions for the development of intelligent CAD.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

How this classification was reachedexpand

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)0.000
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: Methods · Consensus signal: Methods
Teacher disagreement score0.987
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.066
GPT teacher head0.268
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2002
Admission routes2
Has abstractyes

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