Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm
Bibliographic record
Abstract
Identifying trajectories of early white matter development is important for understanding atypical brain development and impaired functional outcomes in children born very preterm (<32 weeks gestational age [GA]). In this study, 161 diffusion images were acquired in children born very preterm (median GA: 29 weeks) shortly following birth (75), term-equivalent (39), 2 years (18), and 4 years of age (29). Diffusion tensors were computed to obtain measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), which were aligned and averaged. A paediatric atlas was applied to obtain diffusion metrics within 12 white matter tracts. Developmental trajectories across time points demonstrated age-related changes which plateaued between term-equivalent and 2 years of age in the majority of posterior tracts and between 2 and 4 years of age in anterior tracts. Between preterm and term-equivalent scans, FA rates of change were slower in anterior than posterior tracts. Partial least squares analyses revealed associations between slower MD and RD rates of change within the external and internal capsule with lower intelligence quotients and language scores at 4 years of age. These results uniquely demonstrate early white matter development and its linkage to cognitive functions.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".