Temporal integration in face perception: Evidence of configural processing of temporally separated face parts.
Bibliographic record
Abstract
Temporal integration is the process by which temporally separated visual components are combined into a unified representation. Although this process has been studied in object recognition, little is known about temporal integration in face perception and recognition. In the present study, the authors investigated the characteristics and time boundaries of facial temporal integration. Whole faces of nonfamous and famous people were segmented horizontally into 3 parts and presented in sequence, with varying interval lengths between parts. Inversion and misalignment effects were found at short intervals (0-200 ms). Moreover, their magnitude was comparable to those found with whole-face presentations. These effects were eliminated, or substantially reduced, when the delay interval was 700 ms. Order of parts presentation did not influence the pattern of inversion effects obtained within each temporal delay condition. These results demonstrate that temporal integration of faces occurs in a temporary and limited visual buffer. Moreover, they indicate that only integrated faces can undergo configural processing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".