Association between pupil constriction and aesthetic preference/naturalness in art-paintings
Bibliographic record
Abstract
Background: Pupil dilation was shown to reflect the extent of preference in Mondrian painting (Johnson et al., 2010). Objective of this study is to investigate whether the pupillary response reflects aesthetic preference/naturalness in art-paintings (Kondo et al., 2017). Method: All paintings used as the stimulus were selected from WikiArt and categorized into "Abstract", "Flower" and "Poster". Observers were presented either original paintings or hue-flipped ones (180 deg rotated in hue angle). Pupil size was recorded monocularly with EyeLink 1000+ (SR Research, Mississauga, ON, Canada) while presentation of paintings. The preference and naturalness for art-paintings were evaluated subjectively by asking observers to rate preference and naturalness with trackball mouse. 18 observers participated in the experiment. Results and Discussions: In all paintings, observers' pupil constriction rate increased while they viewed hue-flipped paintings compared to the original paintings. In addition, original paintings were preferred and perceived more natural compared to hue-flipped paintings. Moreover, significant correlation was found between preference and naturalness. Hence, we performed a regression analysis to examine the relationship between pupil response and other factors (preference, naturalness and lightness (L* in CIELAB)) in each category. For all paintings categories, pupil constriction was influenced by subjective preference and naturalness. However, the results indicated that mean lightness (L*) was effective only in the category "Poster". In other words, pupil was largely influenced by preference and naturalness rather than lightness (L*) in "Abstract" and "Flower" paintings, suggesting that it is possible to evaluate subjective preference and naturalness by pupil response not just for realistic paintings such as "Flower" but also for abstract paintings. Meeting abstract presented at VSS 2018
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".