The Importance of Head Growth Patterns in Predicting the Cognitive Abilities and Literacy Skills of Small-for-Gestational-Age Children
Bibliographic record
Abstract
This study evaluated the effects of head growth compromise beginning in utero and continuing, in some cases, through the first 9 months of life on the cognitive and literacy skills of school-age small-for-gestational-age (SGA) children. Seventy-one SGA children, aged 7 to 9 years (gestational ages, 24-41 weeks) and 16 full-term appropriate-for-gestational-age control children of comparable socioeconomic backgrounds and age at testing completed tests assessing intelligence, receptive language, working memory, problem solving, visual-motor integration, phonological awareness, reading, and spelling. SGA children were subdivided into head-growth pattern groups based on their head circumference at birth and at 9 months postterm. Analyses showed that SGA children with poor prenatal and postnatal head growth had the worst outcomes, followed by those with prenatal brain compromise, but good postnatal head growth. SGA children with preserved head growth in utero as well as good head growth after birth demonstrated the best outcomes, although spelling skills were deficient relative to full-term peers. The Verbal and Full Scale IQ ratings of the SGA children who had experienced brain compromise in utero declined significantly from 5 to 8 years of age. We conclude that mild intrauterine growth retardation (IUGR) has a minimal effect on the development of cognitive or academic abilities, providing that brain growth in utero is not affected. IUGR that slows brain growth in utero impairs the acquisition of some cognitive and academic abilities, even when followed by good catch-up head growth after birth, whereas poor brain growth in utero followed by little or no catch-up head growth results in widespread impairments. Findings highlight the limits to brain plasticity and emphasize the importance of optimal prenatal and postnatal brain growth.
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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 | 0.005 |
| 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) | 0.001 | 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".