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Record W2041653816 · doi:10.1145/2037715.2037729

Rendering Op Art lines

2011· article· en· W2041653816 on OpenAlexaff
Tiffany C. Inglis, Craig S. Kaplan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Technology, and Culture
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConcentricComputer graphics (images)IllusionArtificial intelligenceRendering (computer graphics)Computer scienceOptical illusionComputer visionArtVisual artsMathematicsGeometryPsychology

Abstract

fetched live from OpenAlex

The 1960's marked the start of the Op Art movement. Typically, Op artists make use of optical illusions and high contrast to create artworks that "trick the eye", such as revealing hidden images or inducing a sense of movement. Artist Reginald H. Neal created a piece entitled Square of Two (see Figure 1a) which at first glance is a 2 x 2 tiling of concentric squares that seems to be scintillate as the eye moves across the image. A closer look reveals that the entire image is constructed out of lines arranged in two orthogonal directions, and the boundaries of the concentric squares are actually illusory contours created by the bending of these lines.

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)0.000
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0420.005

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 head0.078
GPT teacher head0.224
Teacher spread0.146 · 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
GenreMethods

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
Published2011
Admission routes1
Has abstractyes

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