MétaCan
Menu
Back to cohort
Record W2188753760 · doi:10.1115/detc2001/dtm-21715

Towards Biomimetic Concept Generation

2001· article· en· W2188753760 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 institutionsUniversity of Toronto
Fundersnot available
KeywordsBiomimeticsComputer scienceNatural (archaeology)PhenomenonBiological engineeringArtificial intelligenceManagement scienceBiochemical engineeringEngineeringEpistemologyBiology

Abstract

fetched live from OpenAlex

Abstract This paper describes efforts towards generalizing biomimetic concept generation in engineering design. Biomimetic design fully or partially imitates or evokes some biological phenomenon. Nature has often inspired solutions to engineering problems. While biological phenomena hold a vast amount of ideas, a method for finding and using these ideas would make biomimetic innovation faster, easier and more accessible. The paper begins with a brief review of related research, recognition of engineering ideas in biological phenomena and advantages of the natural brand. Next presented are strategies for finding potential analogies in biological phenomena, including searching functionally across multiple levels of organization, from the molecule to the biosphere. Initial efforts at finding appropriate analogies are documented using an example in design for remanufacture.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.998

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)0.0030.000

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 head0.040
GPT teacher head0.279
Teacher spread0.239 · 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

Citations76
Published2001
Admission routes1
Has abstractyes

Explore more

Same topicDesign Education and PracticeFrench-language works237,207