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Record W2466040625 · doi:10.1680/jbibn.16.00011

Advancing biomimetic materials through ISO standards

2016· article· en· W2466040625 on OpenAlexaff
Norbert Hoeller, Filippo A. Salustri

Bibliographic record

VenueBioinspired Biomimetic and Nanobiomaterials · 2016
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBiomimeticsStandardizationBiomimetic materialsConsistency (knowledge bases)Engineering managementEngineeringEngineering ethicsComputer scienceFunction (biology)Management scienceNanotechnologySystems engineeringProcess managementKnowledge managementArtificial intelligenceMaterials science

Abstract

fetched live from OpenAlex

This paper discusses the challenges and opportunities of developing standards for biomimetic materials, based on the authors’ experience with International Organization for Standardization (ISO)/Technical Committee 266 ‘Biomimetics’. With the expansion of global trade, international standards are increasingly called on to protect the interests of consumers, improve business productivity and facilitate trade. In the past, standards typically addressed form/fit/function specifications and were associated with mature industries. Some ISO standards are beginning to focus on processes, quality and consistency, which can support advances in emerging fields such as biomimetics. ISO has the potential to advance biomimetic materials and biomimetics in general by developing and promoting frameworks that reflect the evolving nature of biomimetics. Rather than standardizing the output of biomimetics, ISO/TC 266 could explore systemic challenges and identify initiatives to overcome them, such as building an internationally recognized common vocabulary to improve communication within the biomimetics community. An in-depth assessment of research and industry trends relating to biomimetic materials could identify opportunities for collaboration that advance both theory and practice. The goal is to define an appropriate level of structure that accelerates development of biomimetics while at the same time encouraging creativity and exploration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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.

Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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