Visual and emotional salience influence eye movements
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
In natural vision both stimulus features and cognitive/affective factors influence an observer's attention. However, the relationship between stimulus-driven (bottom-up) and cognitive/affective (top-down) factors remains controversial: How well does the classic visual salience model account for gaze locations? Can emotional salience counteract strong visual stimulus signals and shift attention allocation irrespective of bottom-up features? Here we compared Itti and Koch's [2000] and Spectral Residual (SR) visual salience model and explored the impact of visual salience and emotional salience on eye movement behavior, to understand the competition between visual salience and emotional salience and how they affect gaze allocation in complex scenes viewing. Our results show the insufficiency of visual salience models in predicting fixation. Emotional salience can override visual salience and can determine attention allocation in complex scenes. These findings are consistent with the hypothesis that cognitive/affective factors play a dominant role in active gaze control.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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