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Record W2094526331 · doi:10.2495/dne-v4-n3-203-210

Lusciousness, the crafted image in a digital environment

2010· article· en· W2094526331 on OpenAlexvenueno aff
Rob Kesseler

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTRACE (psycholinguistics)Variety (cybernetics)PaintingVisual artsSpectacleThe artsDiversity (politics)Interpretation (philosophy)Space (punctuation)ArtAestheticsComputer scienceSociologyArtificial intelligencePolitical scienceAnthropologyLinguistics

Abstract

fetched live from OpenAlex

With its seemingly endless array of colourful forms and structures, the plant world has inspired generations of artists and illustrators, resulting in a spectacular wealth of paintings and illustrations that have served to inform and captivate its many audiences. Approaches to working from plants refl ect the diversity of source material and the intention of the artist, from the anatomical accuracy for purposes of identifi cation to expressive interpretation. The development of digital imaging within the arts and sciences over the past twenty years has been swift and impressive and its affect on the forms of creation has been marked and unavoidable. We have become as accustomed to viewing images of outer space developed from data sent back from the Hubble Telescope or live views from within the human body. However, in a climate where programmes are constantly being developed to facilitate the production of visual spectacle, the ability to retain the trace of the artist's hand becomes more diffi cult. For the past ten years, the author has worked with botanists at the Royal Botanic Gardens, Kew, exploring the creative potential of plant material at a microscopic level. While working with a variety of microscopic processes and imaging technologies, issues have arisen concerning the status of the fi nal image. The evolution of the work during this period has sought to address some of these issues.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.270

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 integrity0.0000.001
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 head0.008
GPT teacher head0.242
Teacher spread0.233 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicBotanical Research and ApplicationsFrench-language works237,207