Precursors of self‐regulation in infants at elevated likelihood for autism spectrum disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research concerning temperament in children and adults with autism spectrum disorder (ASD) has suggested a consistent profile of low positive affect, high negative affect, and low regulation (Visser et al., 2016). One area receiving less attention is individual differences among children diagnosed with ASD. The primary objective of this study was to use a person-centered approach to explore heterogeneity of early temperament precursors of regulation in a large sample of infants with elevated familial likelihood of ASD. Early precursors of regulation included temperament assessed at 6, 12, and 24 months whereas outcome measures were diagnosis of ASD, cognitive ability and adaptive behavior at 36 months. Participants included 176 low-likelihood and 473 elevated-likelihood infants, 129 of whom were diagnosed with ASD at 3 years. Results supported a three-profile solution: a well-regulated profile (high positive affect and high attentional focus and shifting), a low attention focus profile (higher attentional shifting compared to attentional focus), and a low attention shifting profile (higher attentional focus compared to attentional shifting). A higher proportion of children diagnosed with ASD were classified into the low attention shifting profile. Furthermore, children with the well-regulated profile were differentiated from the other profiles by a pattern of higher social competence and lower dysregulation whereas children with the low attention focus profile were distinguished from the other profiles by higher cognitive ability at 3 years. The findings indicate that the combination of early positive affect with attention measures may provide an enhanced tool for prediction of self-regulation and later outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it