Bibliographic record
Abstract
PURPOSE OF REVIEW: This review highlights the most important developments in the biology and treatment of Merkel cell carcinoma published in the medical literature over the past year. RECENT FINDINGS: Adjuvant radiotherapy to the primary site with or without coverage of the nodal region is recommended in most older series, although a risk-adapted approach is more reasonable. Sentinel lymph node biopsy should be considered in all cases irrespective of primary size. If not feasible, prophylactic regional radiotherapy is recommended as the risk of regional relapse without nodal staging is about 45%. Adjuvant radiotherapy to nodal regions after lymphadenectomy is not studied in detail, but there is a suggestion from many series that the recurrence rate is high enough to justify its use. Recent research has revealed that adjuvant chemotherapy currently has no established role in the treatment of localized node-negative Merkel cell carcinoma. Its use in pathologically node-positive or recurrent cases requires further study. SUMMARY: Given the lack of randomized evidence and heterogeneity in published retrospective series, clinical judgment is required to assess risk factors of an individual patient to make treatment decisions.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".