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Record W2114866420 · doi:10.1162/leon_a_00087

Artistic Exploration of the Worlds of Digital Developmental Swarms

2011· article· en· W2114866420 on OpenAlexaff
Sebastian von Mammen, Thomas Wißmeier, Joyce Wong, Christian Jacob

Bibliographic record

VenueLeonardo · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Technology, and Culture
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSwarm behaviourRule-based machine translationComputer scienceGenerative grammarGrammarCreativityHuman–computer interactionMovement (music)Dynamics (music)Artificial intelligenceVisual artsAestheticsArtSociologyLinguisticsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

This paper presents artwork that was inspired by a computational model called Swarm Grammars. In this work, the “liveliness” of swarms is combined with the generative capabilities of more established developmental representations. Three of the authors followed their individual artistic approaches to explore the creativity and dynamics of Swarm Grammar structures. One chose to breed structures interactively to compose virtual spaces. The second explores the movement and construction dynamics of interactive swarms. The third artist translated developmental processes of Swarm Grammars into interactions of paint particles driven by friction and gravity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.005
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.059
GPT teacher head0.212
Teacher spread0.153 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2011
Admission routes1
Has abstractyes

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