Bibliographic record
Abstract
OBJECTIVE: To review recent advances in radiation therapy in treatment of breast cancer. QUALITY OF EVIDENCE: MEDLINE and CANCERLIT were searched using the MeSH words breast cancer, ductal carcinoma in situ, sentinel lymph node biopsy, and postmastectomy radiation. Randomized studies have shown the efficacy of radiation treatment for ductal carcinoma in situ (DCIS) and for invasive breast cancer. MAIN MESSAGE: Lumpectomy followed by radiation is effective treatment for DCIS. In early breast cancer, shorter radiation schedules are as efficacious for local control and short-term cosmetic results as traditional fractionation regimens. Sentinel lymph node biopsy is done in specialized cancer centres; regional radiation is recommended for patients with four or more positive axillary lymph nodes. Postmastectomy radiation has been shown to have survival benefits for high-risk premenopausal patients. Systemic metastases from breast cancer usually respond satisfactorily to radiation. CONCLUSION: Radiation therapy continues to have an important role in treatment of breast cancer. There have been great advances in radiation therapy in the last decade, but they have raised controversy. Further studies are needed to address the controversies.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".