SELECTIVE ATTENTION SKILLS AND GRAY MATTER DEVELOPMENT IN VERY PRETERM CHILDREN
Bibliographic record
Abstract
Background Attentional functions are thought to rely strongly on frontal and parietal cortex. Studies have shown that preterm birth may lead to an altered pattern of cortical development, but few studies have investigated specific links between developmental changes in the brain and executive skills. Objective To investigate the performance of very preterm (VPT) children on a selective attention task in relation to lobar gray matter development. Methods Children aged 9–10 years were assessed with the sky search selective attention task from the test of everyday attention for children. Brain images were acquired using 1.5 T Philips magnetic resonance imaging (MRI) and were segmented automatically using the Montreal Neurological Institute protocol. Results 46 VPT children (gestational age Conclusions Decreased performance on a selective attention task among very preterm children is particularly related to the growth of both temporal and right occipital lobes; in contrast the anticipated correlation with frontal or parietal lobar volumes was absent. Preterm children may adopt different strategies to term children to complete this task.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".