Synovial Sarcoma: A Clinical Review
Bibliographic record
Abstract
Synovial sarcomas (SS) represent a unique subset of soft tissue sarcomas (STS) and account for 5-10% of all STS. Synovial sarcoma differs from other STS by the relatively young age at diagnosis and clinical presentation. Synovial sarcomas have unique genomic characteristics and are driven by a pathognomonic t(X;18) chromosomal translocation and subsequent formation of the SS18:SSX fusion oncogenes. Similar to other STS, diagnosis can be obtained from a combination of history, physical examination, magnetic resonance imaging, biopsy and subsequent pathology, immunohistochemistry and molecular analysis. Increasing size, age and tumor grade have been demonstrated to be negative predictive factors for both local disease recurrence and metastasis. Wide surgical excision remains the standard of care for definitive treatment with adjuvant radiation utilized for larger and deeper lesions. There remains controversy surrounding the role of chemotherapy in the treatment of SS and there appears to be survival benefit in certain populations. As the understanding of the molecular and immunologic characteristics of SS evolve, several potential systematic therapies have been proposed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".