Learning unfamiliar faces in infants: The advantage of the regular sequence presentation and the three-quarter view superiority
Bibliographic record
Abstract
We investigated the effect of the regular sequence of different views and the three-quarter view effect on the learning of unfamiliar faces by infants. 3–8-month-old infants were familiarized with unfamiliar female faces in either the regular condition (presenting 11 different face views from the frontal view to the left-side profile view in regular order) or the random condition (presenting the same 11 different face views in random order). Following the familiarization, infants were tested with a pair of a familiarized and a novel female face either in a three-quarter (Experiment 1) or in a profile view (Experiment 2). Results showed that only 6–8-month-old infants could identify a familiarized face in the regular condition when they were tested in three-quarter views. In contrast, 6–8-month-old infants showed no significant novelty preference in profile views. The results suggest that the regular sequence of different face views promotes the learning of unfamiliar faces by infants over 6 months old. Moreover, our findings imply that the three-quarter view effect appears in infants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".