Treatment Strategies for Pediatric Intrarenal Ewing Sarcoma: a scoping review protocol
Bibliographic record
Abstract
Objective: This review aims to identify and summarize evidence available for the treatment of kidney Ewing sarcoma in children.Introduction: Renal Ewing sarcoma is a rare tumor with a poor prognosis. Limited studies exist that describe treatment decisions and outcomes related to this highly aggressive malignancy. By mapping the literature, this review may guide management decisions and address knowledge gaps leading to future comparative research studies with higher level of evidence. Inclusion criteria: Studies about renal Ewing sarcoma or primitive neuroectodermal tumor in children (aged 18 years old and below) and the management done with description of the patients' demographics, tumor characteristics and outcomes of treatment will be included. Methods: Medline, Embase, Scopus, Google Scholar and grey literature sources will be searched from database inception to the present. Two reviewers will screen the titles and abstracts of all extracted articles. Any study presenting pediatric patients with Ewing sarcoma and a description of treatment and outcomes will go to full-text screening. Additionally, the reference lists and citing references of all included papers will be checked and citations deemed relevant will go through full-text screening. Any disagreements in citations to be included in the scoping review will be resolved by a third independent reviewer. A PRISMA flow diagram will be utilized to show the screening and selection process of articles. Data from the selected citations will be charted in a table displaying authors(s) and year of publication, patient and tumor characteristics, and treatment approaches tried alongside their outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.047 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.023 | 0.015 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 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".