Effects of repetition and configural changes on the development of face recognition processes
Bibliographic record
Abstract
We investigated the effect of repetition on recognition of upright, inverted and contrast-reversed target faces in children from 8 to 15 years when engaged in a learning phase/test phase paradigm with target and distractor faces. Early (P1, N170) and late ERP components were analysed Children across age groups performed equally well, and were better at recognizing upright faces. However, teenagers and adults were equally accurate for all three face types. The neurophysiological responses to upright, inverted and negative faces matured until adulthood and showed different effects at different ages. P1 and N170 components were affected by face type at all ages, suggesting early configural disruption on encoding processes regardless of age. Frontal ERPs reflected the difficulty of processing these stimuli. Distinct repetition effects were seen at frontal, temporal frontal and parietal sites, suggesting differential involvement of these brain regions underlying working memory and recognition processes. Thus, a learning phase was sufficient (a) for 8-year-olds to perform as accurately as 15-year-olds and (b) to eliminate face type effects in teenagers and adults, but not in younger children.
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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 | 0.000 | 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 | 0.000 |
| 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".