cIMPACT‐NOW: a practical summary of diagnostic points from Round 1 updates
Bibliographic record
Abstract
Abstract cIMPACT‐NOW (the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy) was established to provide a forum to evaluate and recommend proposed changes to future CNS tumor classifications. From 2016 to 2019 (Round 1), cIMPACT published four updates. Update 1 clarified the use of the term NOS (Not Otherwise Specified) and proposed use of the additional term NEC (Not Elsewhere Classified). Update 2 issued clarifications regarding two diagnoses: Diffuse Midline Glioma, H3 K27M‐mutant and Diffuse Astrocytoma/Anaplastic Astrocytoma, IDH‐mutant . Update 3 proposed molecular criteria that could be used in the setting of an IDH‐wildtype diffuse or anaplastic astrocytic glioma without histological features of glioblastoma to infer that the tumor would behave similarly to a grade IV glioblastoma. Update 4 suggested that, in children and young adults, subtypes of IDH‐wildtype/H3‐wildtype diffuse gliomas may have distinct clinical features in the setting of a BRAF V600E mutation, FGFR1 alteration, other MAPK pathway alteration, or a MYB or MYBL1 rearrangement. The practical diagnostic relevance of these cIMPACT proposals is highlighted in this summary.
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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 | 0.023 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.034 | 0.028 |
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".