Following the Masters: Portrait Viewing and Appreciation is Guided by Selective Detail
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.
Bibliographic record
Abstract
A painted portrait differs from a photo in that selected regions are often rendered in much sharper detail than other regions. Artists believe these choices guide viewer gaze and influence their appreciation of the portrait, but these claims are difficult to test because increased portrait detail is typically associated with greater meaning, stronger lighting, and a more central location in the composition. In three experiments we monitored viewer gaze and recorded viewer preferences for portraits rendered with a parameterised non-photorealistic technique to mimic the style of Rembrandt (DiPaola, 2009 International Journal of Art and Technology 2 82-93). Results showed that viewer gaze was attracted to and held longer by regions of relatively finer detail (experiment 1), and also by textural highlighting (experiment 2), and that artistic appreciation increased when portraits strongly biased gaze (experiment 3). These findings have implications for understanding both human vision science and visual art.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 it