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Record W2139568207 · doi:10.1080/13576500903548382

Lateral biases in lighting of abstract artwork

2010· article· en· W2139568207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2010
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPaintingPerceptionQuadrant (abdomen)Artificial intelligenceComputer scienceComputer visionVisual perceptionVisual artsComputer graphics (images)PsychologyArt

Abstract

fetched live from OpenAlex

Previous studies examining perceptual biases in art have revealed that paintings tend to be lit from above and to the left. Abstract images provide a way of testing for the left-light bias while controlling for cues such as posing biases, ground line, shadows, and reflections. A total of 42 participants completed a task that required moving a "virtual flashlight" across the surface of abstract images presented on a computer screen: 20 images (presented both right-side-up and upside down) were used in the study. The participant's only instruction was to "light the painting in a way that is most aesthetically pleasing to you". As predicted, participants on average focused the "virtual flashlight" in the top left quadrant. This study reveals that lateral lighting biases in artwork are not dependent on perception of local light source or interactions with discrete, concrete visual representations in the artwork.

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.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.025
GPT teacher head0.271
Teacher spread0.247 · 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