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Record W2905342886 · doi:10.5527/wjn.v7.i8.155

Clear cell papillary renal cell carcinoma: A case report and review of the literature

2018· article· en· W2905342886 on OpenAlexaboutno aff
Sung Han Kim, Whi‐An Kwon, Jae Young Joung, Ho Kyung Seo, Kang Hyun Lee, Jinsoo Chung

Bibliographic record

VenueWorld Journal of Nephrology · 2018
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNephrectomyPapillary renal cell carcinomasRenal cell carcinomaClear cellImmunohistochemistryPathologyKidneyRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Clear cell papillary renal cell carcinoma (ccpRCC) was recently established as a distinct type of epithelial neoplasm by the International Society of Urological Pathology Vancouver Classification of Renal Neoplasia. Here, we report a case of partial nephrectomy for a ccpRCC detected during the routine follow-up of a previously treated liposarcoma in a 70-year-old male patient. The patient was referred to the urology department for a right-sided renal mass (size: 2 cm) detected during routine annual imaging follow-up for a malignant right inguinal fibrous histocytoma and liposarcoma that had been diagnosed 6 and 4 years earlier, respectively, and treated with surgery and adjuvant radiation therapy. Following partial nephrectomy, the renal mass was pathologically diagnosed as ccpRCC, and immunohistochemistry revealed carbonic anhydrase 9 (CA9) expression. No recurrences or metastases were detected on follow-up imaging for 6 months. This is the first report of partial nephrectomy for incidentally discovered CA9-positive ccpRCC.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.013
GPT teacher head0.253
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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