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Record W2189241744

Implementing and assessing the hybrid ideation space: a cognitive artefact for conceptual design

2007· article· en· W2189241744 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSketchComputer scienceHuman–computer interactionConversationAmbiguityAbstractionProcess (computing)Interface (matter)IdeationRepresentation (politics)CreativityConceptual designArtificial intelligenceCognitive sciencePsychology
DOInot available

Abstract

fetched live from OpenAlex

Actual 3D modelling tools and virtual reality systems are affecting creativity during the early stages of the design process. They are often used as communication tools (passive) rather than ideation tools (active) because of their interface complexity. Among other reasons, this is due to abstract commands that demand precision in the execution and always suggest inconsistent default values. This situation is hindering the representational conversation and cognitive artefacts during the design process. Being adapted to this task, ideation is still being done through analogue tools such as sketches and physical models, which are direct ways of representation with the ambiguity, inaccuracy and abstraction of their intuitive depictions. This paper presents the implementation and evaluation of a new innovative system: the Hybrid Ideation Space. This system allows users to sketch and make models all around them in real-time and in scale using a digital tablet and an immersive projection device.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.215

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 head0.055
GPT teacher head0.356
Teacher spread0.300 · 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

Quick stats

Citations26
Published2007
Admission routes1
Has abstractyes

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