Histopathological study of lesions of the caruncle: a 15-year single center review
Bibliographic record
Abstract
INTRODUCTION: The caruncle is a modified cutaneous tissue located at the inner canthus that contains hair follicles, accessory lacrimal glands, sweat glands and sebaceous glands. These different types of tissues can give rise to a wide variety of lesions that make the clinical diagnosis difficult. The aim of the study was to investigate the most common types of caruncle lesions and the clinical and pathological correlation. METHODS: Retrospective, observational case series. Records of caruncle lesions examined at the Henry C. Witelson Ocular Pathology Laboratory, McGill University, Montreal, Canada, between 1993 and 2008 were analyzed, comparing the clinical and histopathological findings. RESULTS: A total of 42 lesions from 42 patients were analyzed. Twenty-six (61.90%) of the patients were women and 16 (38.10%) were men and the age range from 20 to 84. The main diagnoses were: 16 epithelial lesions (38.09%), 14 inflammatory lesions (31.70%), 10 melanocytic lesions (21,95%), 2 lymphoid lesions (4.87%). From the 28 cases that had a preoperative clinical hypothesis only 17 presented a histopathological confirmation of the diagnosis (60.71%). CONCLUSION: The most common caruncle lesions were epithelial tumors followed by chronic inflammation and melanocytic lesions. Although most of the lesions were benign, there was a great number of misdiagnose based on the clinical suspicious.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".