Rapid face orienting in infants and school-age children with and without autism: Exploring measurement invariance in eye-tracking
Bibliographic record
Abstract
Questions concerning the ontogenetic stability of autism have recently received increased attention as long-term longitudinal studies have appeared in the literature. Most experimental measures are designed for specific ages and functioning levels, yet developing experimental tasks appropriate for a wide range of ages and functioning levels is critical for future long-term longitudinal studies, and treatment studies implemented at different ages. Accordingly, we designed an eye-tracking task to measure preferential orienting to facial features and implemented it with groups of participants with varying levels of functioning: infants, and school-age children with and without autism. All groups fixated eyes first, revealing an early and stable orienting bias. This indicates common bias towards the eyes across participants regardless of age or diagnosis. We also demonstrate that this eye-tracking task can be used with diverse populations who range in age and cognitive functioning. Our developmental approach has conceptual implications for future work focused on task development and particularly new experimental measures that offer measurement equivalence across broad age ranges, intellectual functioning and verbal abilities.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".