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Record W2569254611 · doi:10.5489/cuaj.4292

Treatment options in advanced renal cell carcinoma after first-line treatment with vascular endothelial growth factor receptor tyrosine kinase inhibitors

2016· review· en· W2569254611 on OpenAlexaffvenue
Naveen S. Basappa

Bibliographic record

VenueCanadian Urological Association Journal · 2016
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCabozantinibAxitinibEverolimusLenvatinibMedicineRenal cell carcinomaSunitinibNivolumabVascular endothelial growth factorPazopanibOncologyTargeted therapyTyrosine-kinase inhibitorTyrosine kinaseInternal medicineCancer researchVEGF receptorsSorafenibImmunotherapyReceptorCancer

Abstract

fetched live from OpenAlex

Targeted therapy for metastatic renal cell carcinoma (mRCC) was introduced a decade ago and since then, a number of therapeutic options have been developed. Vascular endothelial growth factor-targeted therapy is the widely accepted first-line option for mRCC. After progression, treatment in the second-line setting has typically been with either axitinib or everolimus. However, with the advent of several new agents demonstrating efficacy in the second-line setting, including nivolumab, cabozantinib, and the combination of lenvatinib and everolimus, the treatment paradigm has shifted toward these novel therapies with improved patient outcomes.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.241
Teacher spread0.221 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2016
Admission routes2
Has abstractyes

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