Childhood Medulloblastoma
Bibliographic record
Abstract
Medulloblastoma is the most common malignant brain tumour in children and is a major cause of mortality and morbidity, particularly in low- and middle-income countries. It has been risk-stratified on the basis of clinical (age, metastasis and extent of resection) and histological subtypes (classic, desmoplastic and anaplastic). However, recently medulloblastoma has been sub-grouped by using a variety of different genomic approaches, such as gene expression profiling, micro-ribonucleic acid profiling and methylation array into 4 groups, namely Wingless, Sonic hedgehog, Group 3 and Group 4. This new sub-grouping has important therapeutic and prognostic implications. After acute leukaemia, brain tumour is the second most common malignancy in the paediatric age group. The improvement in outcome of acute lymphoblastic leukaemia in low- and middle-income countries reflects the relative simplicity of diagnostic procedures and management. Unlike leukaemia, the management of brain tumours requires a complex multidisciplinary approach, including neuro-radiologists, neurosurgeons with a paediatric expertise, neuropathologists, radiation oncologists and neuro-oncologists. In addition, the equipment required for the diagnosis (magnetic resonance imaging scan, histological, molecular and genetic techniques) and the management (operating room, radiation facilities) is a limiting factor in countries with limited resources. In Pakistan, there are very few centres able to treat children with brain tumours. The current literature review was planned to provide an update on the management of this tumour.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".