White matter microstructure abnormalities in children experiencing neglect without other forms of maltreatment
Bibliographic record
Abstract
Childhood maltreatment can disrupt brain development, leading to vulnerabilities in white matter (WM) microstructure, compromised brain integrity, and various psychiatric disorders. Among different forms of maltreatment, neglect is the most common; however, limited data exist on its specific impact on the brain. This study utilized diffusion tensor imaging to examine WM microstructure differences between neglected children without other types of maltreatment (Neglect, n = 21) and typically developing controls (TD, n = 106). Additionally, the study explored the relationship between WM microstructure alterations and psychosocial problems observed in neglected children. Neglected children exhibited larger axial diffusion (AD) in regions such as the right corticospinal tract (R.CST), right superior longitudinal fasciculus (R.SLF), and left cingulum (L.CG) compared to typically developing children. Increased AD in the R.CST, L.CG, and R.SLF was associated with conduct problems. These findings suggest that alterations in WM microstructure contributed to behavioral symptoms in neglected children.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".