Bibliographic record
Abstract
Merkel cell carcinoma (MCC) is a rare primary cutaneous neuroendocrine carcinoma with a high mortality rate. It typically affects elderly Caucasians, with a slight predilection for males. It is associated with chronic sun exposure and/or immunosuppression. Almost half of all cases occur on the head or neck and an estimated 2.5%–10% arise on the eyelids or periocular skin. It ranks as the 5 th most common malignant tumor at these sites, preceded in frequency by basal cell, squamous cell and sebaceous carcinoma, as well as melanoma. Its clinical presentation as a violaceous nodule/plaque lacks specificity, and it can be mistaken for cysts, chalazia or basal cell carcinomas. Sub-specialized histopathological and immunohistochemical evaluations are required for diagnosis. Clinical staging defines the extent of disease and governs management. This includes surgery and adjuvant radiotherapy for localized tumors and of late, immunotherapy for metastatic disease. Significant advances in our understanding of the dual etiopathogenesis (Merkel cell polyomavirus- and Ultraviolet radiation-induced) and the biology of the neoplasm have been achieved in recent years. Issuing from the tumor's known susceptibility to host immunity, a recent therapeutic breakthrough has occurred whereby immune checkpoint inhibition has been shown to mitigate advanced disease. These factors and the increased global incidence of the tumor have brought it to the forefront of medical attention. This review provides a clinically relevant update on MCC, with special reference to cases arising on the eyelid/periocular region.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".