SURGICAL MANAGEMENT OF RARE TUMORS (Part 1)
Bibliographic record
Abstract
With an annual cumulative occurrence of approximately 15,000 in North America, all childhood cancers are rare. Very rare cancers as defined by both the European Cooperative Study Group for Rare Pediatric Cancers (EXPeRT) and the Children’s Oncology Group (COG) fall into two principal categories: those so uncommon (fewer than 2 cases/million) that their study is challenging even through cooperative group efforts (e.g. pleuropulmonary blastoma, desmoplastic small round cell tumor) and those that are far more common in adults and therefore rarely studied in children (e.g. thyroid, melanoma, gastrointestinal stromal tumor). [1](#ref-0001) Treatment strategies for these latter tumors are typically based on adult guidelines, although the pediatric variants of these tumors may harbor different genetic signatures and demonstrate different behavior. If melanoma and differentiated thyroid cancer are excluded, other rare cancer types account for only 2% of the cancers in children aged 0 to 14.[1](#ref-0001) This article highlights several of the most common rare tumor types.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".