Value of Immunohistochemistry to Differentiate Digital Papillary Adenocarcinoma From Acral Hidradenoma With Papillary Structures
Bibliographic record
Abstract
ABSTRACT: Digital papillary adenocarcinoma is a malignant adnexal tumor with a predilection for acral sites. Hidradenoma is a benign solid and cystic sweat gland neoplasm with focal ductal and glandular differentiation and good outcomes. Hidradenomas can occur at acral sites and show papillary structures; for this reason, they are included in the differential diagnosis of digital papillary adenocarcinoma, and immunohistochemistry is a valuable tool in this scenario. We described a case of a 43-year-old man with an epithelial tumor showing papillary structures in the intermediate phalanx of the fourth finger. There was diffuse positivity for p63 and negativity for S100 protein, suggesting that this tumor was an acral hidradenoma with papillary structures.
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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) | 0.001 | 0.000 |
| 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".