Disorders of cerebellar growth and development
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review summarizes for the pediatrician the current understanding of normal cerebellar and brainstem development, and then discusses selected malformations to highlight advances in the area. The impact of prematurity on cerebellar growth and development is then examined. The important insights provided by recent neuroimaging and genetic advances are reviewed. RECENT FINDINGS: Previous areas of dispute are being addressed by advances in two major areas. Advanced neuroimaging studies during fetal and postnatal life are now providing important insights into the nature of normal and abnormal development of the brainstem and cerebellum. These powerful new techniques for defining morphology in vivo, together with major advances in genetics, are accelerating our understanding of genotype-phenotype relationships. Conversely, the ability to link early brain injury to subsequent cerebellar development has challenged previous understanding of the distinction between acquired and primary dysgenesis, presumed to be genetic in origin. SUMMARY: The synthesis of a rational and clinically useful classification of posterior fossa malformations has been elusive. Recent developments promise to resolve ongoing disputes that have delayed progress. However, these insights into disturbed structural development demand rigorous examination of their long-term functional significance and caution before their prognostic significance is applied clinically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".