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Record W1748266548 · doi:10.5489/cuaj.2863

Sorafenib treatement for recurrent stage T1 bilateral renal cell carcinoma in patients with Von Hippel- Lindau disease: A case report and literature review

2015· article· en· W1748266548 on OpenAlexvenueno aff
Kyung Hwa Choi, Young Dong Yu, Moon Hyung Kang, Dong Soo Park

Bibliographic record

VenueCanadian Urological Association Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSorafenibMedicineRenal cell carcinomaVon Hippel–Lindau diseaseDiseaseRadiofrequency ablationStage (stratigraphy)Renal functionProgressive diseaseClear cellInternal medicineOncologyRadiologyUrologyAblationHepatocellular carcinoma

Abstract

fetched live from OpenAlex

Renal cell carcinoma (RCC) with Von Hippel-Lindau (VHL) syndrome is associated with multiple recurrences and a young age at diagnosis. Therefore the primary goal of treatment is to stabilize the disease, minimizing the surgical resection and preserving the renal function in the patients with VHL who have developing RCC nodules after initial treatment. This is the first case report of VHL disease, with long-term stable disease, treated with a half dose of sorafenib after surgical resection and radiofrequency ablation for multiple recurrent stage T1 masses. We discuss the efficacy and safety of low-dose sorafenib treatment and review RCC in a patient with VHL disease.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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