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Record W2130735995 · doi:10.1162/leon.2008.41.1.6

Art Embodies A-Life: The VIDA Competition

2008· article· en· W2130735995 on OpenAlexaff
Nell Tenhaaf

Bibliographic record

VenueLeonardo · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsYork University
Fundersnot available
KeywordsStudioCompetition (biology)PopularityVisual artsArtSelection (genetic algorithm)Art historyPerformance artAestheticsComputer scienceArtificial intelligencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Artificial Life artworks hold a unique place in the art world, one that has been largely mapped by the VIDA international competition through its annual recognition of outstanding works based on A-Life. Works that have received awards since the VIDA competition began in 1999 (25 prize-winning artworks and 56 honorary mentions) have gained viewer appreciation and popularity at the same level as any other kind of art. Yet these works define a territory of their own, delineated here through characteristics of A-Life art that arise from both the artist's studio and the research lab and that mark the 25 awarded artworks. Following this article, the Leonardo VIDA Gallery presents a selection of eight prize-winning works that show the breadth of the competition to date; each is discussed here.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.002
Scholarly communication0.0120.002
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0480.011

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 head0.023
GPT teacher head0.241
Teacher spread0.218 · 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
GenreOther

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

Citations12
Published2008
Admission routes1
Has abstractyes

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