Cerebellar Cleft: Confirmation of the Neuroimaging Pattern
Bibliographic record
Abstract
We recently described the neuroimaging and clinical findings in 6 children with cerebellar clefts and proposed that they result from disruptive changes following prenatal cerebellar hemorrhage. We now report an additional series of 9 patients analyzing the clinical and neuroimaging findings. The clefts were located in the left cerebellar hemisphere in 5 cases, in the right in 3, and bilaterally in one child who had bilateral cerebellar hemorrhages as a preterm infant at 30 weeks gestation. In one patient born at 24 weeks of gestation a unilateral cerebellar hemorrhage has been found at the age of 4 months. Other findings included disordered alignment of the folia and fissures, an irregular gray/white matter junction, and abnormal arborization of the white matter in all cases. Supratentorial abnormalities were found in 4 cases. All but 2 patients were born at term. We confirm the distinct neuroimaging pattern of cerebellar clefts. Considering the documented fetal cerebellar hemorrhage in our first series, we postulate that cerebellar clefts usually represent residual disruptive changes after a prenatal cerebellar hemorrhage. Exceptionally, as now documented in 2 patients, cerebellar clefts can be found after neonatal cerebellar hemorrhages in preterm infants. The short-term outcome in these children was variable.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".