The association between social emotional development and symptom presentation in autism spectrum disorder
Bibliographic record
Abstract
Understanding differences in social-emotional behavior can help identify atypical development. This study examined the differences in social-emotional development in children at increased risk of an autism spectrum disorder (ASD) diagnosis (infant siblings of children diagnosed with the disorder). Parents completed the Brief Infant-Toddler Social-Emotional Assessment (BITSEA) to determine its ability to flag children with later-diagnosed ASD in a high-risk (HR) sibling population. Parents of HR (n = 311) and low-risk (LR; no family history of ASD; n = 127) children completed the BITSEA when their children were 18 months old and all children underwent a diagnostic assessment for ASD at age 3 years. All six subscales of the BITSEA (Problems, Competence, ASD Problems, ASD Competence, Total ASD Score, and Red Flags) distinguished between those in the HR group who were diagnosed with ASD (n = 84) compared to non-ASD-diagnosed children (both HR-N and LR). One subscale (BITSEA Competence) differentiated between the HR children not diagnosed with ASD and the LR group. The results suggest that tracking early social-emotional development may have implications for all HR children, as they are at increased risk of ASD but also other developmental or mental health conditions.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".