Untangling the relationships between autism spectrum disorder and non-genetic risk factors
Bibliographic record
Abstract
Autism spectrum disorder (ASD) has been attributed to genetic and non-genetic risk factors. Of the non-genetic factors, prenatal and perinatal complications have been extensively investigated, though few associations have been replicated consistently. We selected 2,562 families with at least one individual with ASD and one unaffected sibling. We investigated the relationships between 29 prenatal and perinatal complications and ASD, while considering the influences of confounding factors, comorbid conditions, and different ASD definitions. Although many complications were associated with ASD in the pairwise comparisons, only haematological disorders of the newborn and lower Apgar scores remained significant after adjusting for the effects of the confounders. After removing individuals with congenital anomalies, only 5-minute Apgar scores were associated with ASD. In conclusion, after considering confounding effects and four ASD definitions, several perinatal complications were associated with ASD with moderate effect sizes. Furthermore, comorbid conditions with ASD appear to be intertwined in these relationships.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".