The informational correlates of conscious and nonconscious face-gender perception
Bibliographic record
Abstract
We used a face-gender repetition priming paradigm to precisely map the spatial frequencies (SFs) that influence observers' responses under different prime awareness conditions. A visible prime condition was set up by presenting the stimulus sequence mask-blank-prime-blank-mask-target and an invisible prime condition by switching the order of the masks and the blanks (see also Dehaene et al., 2001). The prime faces (~4.6° × 3.1°) were randomly filtered trial-by-trial according to the SF bubbles technique (Willenbockel, Fiset et al., 2010). Classification vectors, derived by summing the SF filters from each trial weighted by observers' transformed response times, revealed that SFs around 12 cycles per face width modulated responses in both prime awareness conditions. The significant SFs closely matched those optimal for accurate performance in a direct face-gender classification paradigm. Surprisingly, the significant SFs facilitated observers' responses in the visible prime condition, whereas they slowed responses in the invisible prime condition. Our findings suggest that SF tuning per se remains robust under different prime awareness conditions but that diagnostic visual cues might be utilized in a qualitatively different fashion as a function of awareness.
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.
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) | 0.002 | 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".