cIMPACT‐NOW update 7: advancing the molecular classification of ependymal tumors
Bibliographic record
Abstract
Advances in our understanding of the biological basis and molecular characteristics of ependymal tumors since the latest iteration of the World Health Organization (WHO) classification of CNS tumors (2016) have prompted the cIMPACT-NOW group to recommend a new classification. Separation of ependymal tumors by anatomic site is an important principle of the new classification and was prompted by methylome profiling data to indicate that molecular groups of ependymal tumors in the posterior fossa and supratentorial and spinal compartments are distinct. Common recurrent genetic or epigenetic alterations found in tumors belonging to the main molecular groups have been used to define tumor types at intracranial sites; C11orf95 and YAP1 fusion genes for supratentorial tumors and two types of posterior fossa ependymoma defined by methylation group, PFA and PFB. A recently described type of aggressive spinal ependymoma with MYCN amplification has also been included. Myxopapillary ependymoma and subependymoma have been retained as histopathologically defined tumor types, but the classification has dropped the distinction between classic and anaplastic ependymoma. While the cIMPACT-NOW group considered that data to inform assignment of grade to molecularly defined ependymomas are insufficiently mature, it recommends assigning WHO grade 2 to myxopapillary ependymoma and allows grade 2 or grade 3 to be assigned to ependymomas not defined by molecular status.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".