Bibliographic record
Abstract
A renal cell carcinoma is the ninth most common carcinoma in male and fourteenth most common carcinoma in female population, with continuing increase of incidence rate in the last thirty years. More common use of imaging techniques in diagnostics, has led to discovering great number of renal cell carcinomas while they are still in the asymptomatic phase of their growth. The symptoms of renal neoplasm which often lead to diagnosis of renal cell carcinoma are flank pain, hematuria and palpable abdominal mass. Clear cell renal cell carcinoma is the most common subtype whereas proportion of unclassified renal cell carcinoma is between 0.7 – 5.7%. Compared with clear cell renal cell carcinoma, unclassified renal cell carcinomas are more likely to show aggressive clinical behavior with fatal outcome. Within the category of unclassified renal cell carcinomas, certain carcinomas have profiled as distinct pathologic entities due to improvements of pathologic diagnostic methods. They have been recognized and characterized by The International Society of Urological Pathology which has proposed new renal neoplasia classification known as Vancouver Classification of Renal Neoplasia. The aim of this classification, published in 2013, is to suggest modifications to the World Health Organization 2004 categories. The purpose of this paper is to describe eight subtypes of renal cell carcinomas, which are characterized as distinct entites in the Vancouver classification, but since February 2016, according to the WHO classification of renal cell carcinomas, categorized as unclassified renal cell carcinomas. The new WHO Classification of Tumors of the Urinary System, published in February 2016, officially recognized them as distinct diagnostic entities. This paper is dealing with their epidemiologic, morphologic, immunohistochemical and cytogenetic features.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.016 |
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".