Cross-modal interactions of faces, voices and names in person familiarity
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
Person recognition often involves integration of several cues. We asked if familiarity judgments for one cue were influenced by the congruency of pairings with other cues. In a learning phase, subjects studied audiovisual clips of faces, voices and names. A test phase presented uni-modal and bi-modal stimuli. For 10 subjects the bi-modal test stimuli were faces and voices, for 10 faces and names, and for 10 voices and names. In one set of blocks the target was the first modality, and in the other set it was the second. Targets in bi-modal stimuli were paired with either the same or a different identity in the second modality. Face/voice combinations showed congruency effects in reaction time but face/name and voice/name combinations did not. There was no difference between faces modulating target voices and voices modulating target faces. This is consistent with interactions between sensory representations before amodal stages of person recognition.
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.
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