Immunohistochemical screening for the diagnosis of succinate dehydrogenase-deficient renal cell carcinoma and fumarate hydratase-deficient renal cell carcinoma
Bibliographic record
Abstract
Renal tumors represent heterogeneous and diverse group of neoplasms. The 2013 Vancouver classification of renal tumors and the subsequent 2016 WHO classification represent the foundation of our current knowledge on renal tumors (1). Recent advances have significantly contributed to expanding the morphologic, immunohistochemical, molecular, epidemiologic and clinical features of several novel and emerging renal tumors (2). For example, new evidence has recently emerged on two renal entities—succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) and fumarate hydratase-deficient RCC (FH-deficient RCC). The awareness of these novel renal neoplasms is not only essential for practicing pathologists, but also for clinicians and for patient management, because the navigation through this complex and evolving field is a challenging one, even in centers with large volumes of renal tumors. Importantly, the recognition of these novel renal entities rests mainly on their morphologic recognition, with the aid of immunohistochemistry (IHC).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".