Child Neurology: Cortical Malformations in Preterm Infants
Bibliographic record
Abstract
Malformations of cortical development (MCD) are a rare group of disorders with heterogeneous clinical, neuroimaging, and genetic features. MCD consist of disruptions in the development of the cerebral cortex secondary to genetic, metabolic, infectious, or vascular etiologies. MCD are typically classified by stage of disrupted cortical development as secondary to abnormal: (1) neuronal proliferation or apoptosis, (2) neuronal migration, or (3) postmigrational cortical development. MCD are typically detected with brain MRI when an infant or child becomes symptomatic, presenting with seizures, developmental delay, or cerebral palsy. With recent advances in neuroimaging, cortical malformations can be detected using ultrasound or MRI during the fetal period or in the neonatal period. Of interest, preterm infants are born at a time when many cortical developmental processes are still occurring. However, there is a paucity of literature describing the neonatal imaging findings, clinical presentation, and evolution over time of cortical malformations in preterm infants. In this study, we present the neuroimaging findings from early life to term-equivalent age and childhood neurodevelopmental outcomes of an infant born very preterm (<32 weeks' postmenstrual age) with MCD detected incidentally on neonatal research brain MRI. These brain MRIs were performed as part of a prospective longitudinal cohort study of 160 very preterm infants; MCD were detected incidentally in 2 infants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".