Temporal dynamics of the face familiarity effect: bootstrap analysis of single-subject event-related potential data
Why this work is in the frame
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Bibliographic record
Abstract
Prior event-related potential studies using group statistics within a priori selected time windows have yielded conflicting results about familiarity effects in face processing. Our goal was to evaluate the temporal dynamics of the familiarity effect at all time points at the single-subject level. Ten subjects were shown faces of anonymous people or celebrities. Individual results were analysed using a point-by-point bootstrap analysis. While familiarity effects were less consistent at later epochs, all subjects showed them between 130 and 195 ms in occipitotemporal electrodes. However, the relation between the time course of familiarity effects and the peak latency of the N170 was variable. We concluded that familiarity effects between 130 and 195 ms are robust and can be shown in single subjects. The variability of their relation to the timing of the N170 potential may lead to underestimation of familiarity effects in studies that use group-based statistics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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