Error‐monitoring in response to social stimuli in individuals with higher‐functioning Autism Spectrum Disorder
Bibliographic record
Abstract
Error-monitoring, or the ability to recognize one's mistakes and implement behavioral changes to prevent further mistakes, may be impaired in individuals with Autism Spectrum Disorder (ASD). Children and adolescents (ages 9-19) with ASD (n = 42) and typical development (n = 42) completed two face processing tasks that required discrimination of either the gender or affect of standardized face stimuli. Post-error slowing and the difference in Error-Related Negativity amplitude between correct and incorrect responses (ERNdiff ) were used to index error-monitoring ability. Overall, ERNdiff increased with age. On the Gender Task, individuals with ASD had a smaller ERNdiff than individuals with typical development; however, on the Affect Task, there were no significant diagnostic group differences on ERNdiff . Individuals with ASD may have ERN amplitudes similar to those observed in individuals with typical development in more social contexts compared to less social contexts due to greater consequences for errors, more effortful processing, and/or reduced processing efficiency in these contexts. Across all participants, more post-error slowing on the Affect Task was associated with better social cognitive skills.
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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 | 0.004 |
| 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 | 0.000 |
| 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".