Social and executive functioning in individuals with autism spectrum disorder without intellectual disability: The case–control study protocol of the CNeSA study
Bibliographic record
Abstract
Several studies suggest that children and adolescents with autism spectrum disorder (ASD) often present deficits in executive functions (EFs). The research on cold EF shows a high heterogeneity across different cohorts of patients as well as different study designs, while studies investigating hot EF and their relationship with different ASD phenotypes are still limited and related only to specific domains, although this concept could contribute to clarify the phenotypical variability by explaining the difficulties encountered by individuals with ASD in daily life, where stimuli are often emotionally charged. With the aim to identify specific neuropsychological profiles in children and adolescents with ASD without intellectual disability, we designed a study protocol comparing a clinical sample of individuals with ASD to aged-matched (10–17 years) typically developing controls (TDC) on a neuropsychological test battery investigating both “cold” and “hot” EF with the purpose of further investigating their relationships with ASD symptoms. Autonomic measures including heart rate, heart rate variability, skin conductance, and salivary cortisol were also recorded before/during/after the neuropsychological testing session. This paper describes the case–control study protocol named “Caratterizzazione NEuropsicologica del disturbo dello Spettro Autistico, senza Disabilità Intellettiva, CNeSA study,” its rationale, the specific outcome measures, and their implications for the clinical management of individuals with ASD and a precision medicine approach.
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".