Controversial Indications for Sentinel Lymph Node Biopsy in Breast Cancer Patients
Bibliographic record
Abstract
Sentinel lymph node biopsy (SLNB) emerged in the 1990s as a new technique in the surgical management of the axilla for patients with early breast cancer, resulting in lower complication rates and better quality of life than axillary lymph node dissection (ALND). Today SLNB is firmly established in the armamentarium of clinicians treating breast cancer, but several questions remain. The goal of this paper is to review recent work addressing 4 questions that have been the subject of debate in the use of SLNB in the past few years: (a) What is the implication of finding micrometastases in the sentinel nodes? (b) Is ALND necessary in all patients who have a positive SLNB? (c) How accurate is SLNB after neoadjuvant therapy? (d) Can SLNB be used to stage the axilla in locally recurrent breast cancer following breast surgery with or without prior axillary surgery?
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".