Bibliographic record
Abstract
The axillary lymph node status is the most reliable prognostic indicator of recurrence and overall survival in patients with breast cancer. The current standard surgical procedure for the management of invasive breast cancer is the complete removal of the cancer with total axillary clearance. However, recently, selective sentinel lymph node mapping and biopsy is gaining acceptance as a useful and accurate staging procedure, as it is minimally invasive. The sentinel lymph node is the first node into which a primary cancer drains, and is thus the first node to be involved by metastases. Patients whose sentinel nodes are negative for breast cancer metastases, can be spared a more extensive axillary lymph node dissection, with reduction in the postoperative morbidity. Sentinel node mapping is usually performed by intradermal or peritumoral injection of a combination of blue dye and radiotracer. Sentinel node examination is sometimes done intraoperatively, by imprint cytology and frozen sections, for an immediate assessment, to plan the extent of surgery at a single sitting. Permanent sections of the sentinel node are studied by serial sectioning, and immunohistochemistry for cytokeratin is done to detect micrometastases which are frequently missed on hematoxylin and eosin (H&E)-stained sections. The various aspects of sentinel node examination, and its role to decide further management in patients with ductal carcinoma-in-situ, and in other clinical settings, are discussed in this review.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".