TBIO-30. MOLECULAR LANDSCAPE AND CLINICAL CORRELATIONS OF CNS SARCOMAS
Bibliographic record
Abstract
Central nervous system (CNS) sarcomas are rare mesenchymal tumors accounting for less than 0.2% of intracranial (IC) tumors. Due to their rarity molecular insights they may be misdiagnosed as embryonal brain tumors, thus best clinical approach has been lacking 17 IC and 4 extracranial (EC) sarcomas were examined using methylation profiles and RNASeq analyses to define molecular features and clinicopathologic correlations. CNS sarcomas segregate into 3 sub-groups; the majority exhibited CIC (n=17) or EWS (n=9) fusions, a small subset (n=3) has no defining alteration. All IC EC sarcomas with the same molecular alterations indicating they were not distinct brain tumor types. Median age was 4.25-yrs, 10.6-yrs and 14-yrs for the CIC, EWS and undifferentiated subgroup respectively. The 5-yr PFS was 33%, 75% and 100% and OS was 49%,83% and 100% for the CIC, EWS and undifferentiated group respectively. IC and EC sarcomas represent a common molecular diseases, and should be treated using similar approaches.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".