Fine‐needle aspiration as a diagnostic technique in 50 cases of primary Ewing sarcoma/peripheral neuroectodermal tumor. Institut Curie's experience
Bibliographic record
Abstract
Fine-needle aspiration (FNA) followed by a core-needle biopsy during general anesthesia is a method for diagnosing pediatric tumors in our Institute. To complete the diagnosis in the case of round cell sarcomas, cytology material is also used for genomic analyses, that is, karyotyping and molecular biology-derived techniques. Fifty primary Ewing sarcomas/peripheral neuroectodermal tumors (ES/PNET) in 50 patients were sampled. Cytological diagnoses were "malignant" in all cases and accurate (ES/PNET) in 46 (92%). Two (4%) cases were misdiagnosed as neuroblastoma, and two others (4%) as rhabdomyosarcoma and nephroblastoma. No suspicious or false-negative results were rendered. Karyotyping was performed in 20 (40%) cases and was interpretable in 17 cases but not in three cases. Molecular search for ES/PNET fusion transcripts were performed in all cases and were detected in 44 (88%) cases, but not in six (12%) cases. In conclusion, FNA assisted by genomic techniques is powerful methods to accurate diagnose ES/PNET.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".