Behavioural correlates of atypical brain morphology in individuals with high levels of autistic-like traits
Bibliographic record
Abstract
The current study investigated whether atypical brain morphology extends to individuals in the normal population who are high in autistic-like traits.More specifically, it was hypothesised that autistic-like traits would be negatively correlated with hemispheric lateralization and communication.Additionally, males and individuals enrolled in mathematically intensive university programs were expected to display higher levels of autistic-like traits than females and individuals enrolled in less mathematically intensive programs.A sample of 130 university students completed the AQ questionnaire and three measures of brain morphology to assess autistic-like traits as well as hemispheric lateralization and communication.The results indicated that autistic-like traits in general were not associated with measures of hemispheric lateralization or communication.Only the university program in which the participants were enrolled yielded significant group differences on the AQ.It was concluded that the selected measures were not sensitive enough to detect atypical brain morphology differences in the present sample or that these differences do not exist in subclinical populations.
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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 | 0.002 |
| 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) | 0.002 | 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".