Histopathological review of sebaceous carcinoma of the eyelid
Bibliographic record
Abstract
BACKGROUND: Sebaceous carcinoma of the eyelid can clinically mimic benign conditions, such as recurrent chalazion and inflammation and histopathologically squamous cell and basal cell carcinoma (BCC). This retrospective study was undertaken as an attempt to improve the characterization and consequently the diagnosis of these tumors. METHODS: Retrospective analysis was performed on eyelid specimens diagnosed as sebaceous carcinoma retrieved from Henry C. Witelson Ophthalmic Pathology Registry, Canada and Hospital Luis S. Bulnes Pathology Registry, Mexico. Two independent, masked pathologists reviewed the H&E microslides. RESULTS: Forty-four cases were retrieved, 31 from Canada and 13 from Mexico. Cytoplasmic vacuoles were observed in 48% of the cases. Eighty-four percent of the cases were classified as poorly differentiated lesions. Of these, 75% had features similar to squamous cell carcinoma (SqCC), some with dyskeratosis (30%) and 7% resembled BCC. Solid growth pattern was seen in 26.2% of the cases and lobular growth pattern in 26.2%. Superficial spread resembling Bowen-like disease was observed in 33% of the cases, pagetoid features in 33% and comedocarcinoma in 31.8%. CONCLUSION: Sebaceous carcinoma presented as a poorly differentiated lesion in most cases of this series, which suggests a possibility of misdiagnosis because of its similarities to SqCC.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".