Neuroimaging Insights into Brain Mechanisms of Early-onset Restrictive Eating Disorders
Bibliographic record
Abstract
Background: Early-onset restrictive eating disorders (rEO-ED) encompass a heterogeneous group of conditions, including early-onset anorexia nervosa (EO-AN) and avoidant restrictive food intake disorders (ARFID). Almost nothing is known about the consequences of rEO-ED on brain development. Methods: We performed the largest comparison of MRI-derived brain features in children and early adolescents (<13 years) with EO-AN (n=124), ARFID (n=50), and typically developing individuals (TD, n=112). Results: Despite similar body mass index (BMI) distributions, EO-AN and ARFID showed divergent structural patterns, suggesting independent brain mechanisms. Half the regional brain measures were correlated with BMI in EO-AN and none in ARFID, indicating a partial mediation of EO-AN signal by BMI. EO-AN was associated with a widespread pattern of thinner cortex, while underweight ARFID patients exhibited smaller surface area and subcortical volumes than TD. Conclusion: . ED mechanisms in neurodevelopmental disorders.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".