American Brachytherapy Society (ABS) consensus statement for sarcoma brachytherapy
Bibliographic record
Abstract
PURPOSE: To present recommendations for the use of brachytherapy (BT) in patients with soft tissue sarcoma (STS). METHODS: A group of practitioners with expertise and experience in sarcoma BT formulated recommendations for BT in STS based on clinical experience and literature review. RESULTS: The indications for adjuvant BT are discussed. There is no consensus on the use of BT alone or in combination with external beam radiation therapy (EBRT), but factors that influence the selection of this modality include tumor grade and size, prior surgeries, and tumor recurrence. Low-dose-rate, high-dose-rate, and pulsed-dose-rate radiation are all acceptable BT modalities to use for STS. Recommendations are made for patient selection, techniques, dose rates, and dosages. Outcome data and toxicity data are reviewed. CONCLUSIONS: BT is a useful component of the treatment of STS. The advantages of BT are the targeted dose distribution, low integral dose, and short treatment times. Ultimately the clinician should select the modality or combination of modalities that are most familiar to the treatment team and suitable to the patient.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".