Change detection in an attended face depends on the expectation of the observer
Bibliographic record
Abstract
Sensitivity to a scene change during a brief interruption depends critically on a match between what the observer expects to see and the kind of change that occurs (Austen & Enns, 2000). The present study tested the generality of this conclusion using human faces, which are both socially more relevant and perceptually more configural than the compound letters tested previously. An experiment using the flicker technique examined sensitivity to two types of change: facial identity and emotional expression. Change detection was assessed when attention was either focused or distributed, the change was either expected or unexpected, and the faces were either upright or inverted. The main finding was that detection was expectation-dependent, even when only a single upright face was presented. Secondary findings with regard to attentional distribution and face inversion confirmed that observers were indeed engaged in face processing. We conclude that observer expectations critically influence the perception of single and fully attended human faces.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".