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Record W1483755438

Efficacy and safety of temsirolimus in renal cell carcinoma

2015· article· en· W1483755438 on OpenAlexaboutno aff
Soundouss Raissouni, Richard M. Lee‐Ying, Michael M. Vickers

Bibliographic record

VenueJournal of symptoms and signs · 2015
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsTemsirolimusRenal cell carcinomaMedicineOncologyCancer researchPI3K/AKT/mTOR pathwayInternal medicineCancerKinasePharmacologyDiscovery and development of mTOR inhibitorsBiologySignal transduction
DOInot available

Abstract

fetched live from OpenAlex

Temsirolimus is a novel intravenous targeted therapy that inhibits the mammalian target of rapamycin kinase. This kinase is a part of the phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin pathway, which plays a key role in cell proliferation, metabolism and angiogenesis. Temsirolimus has shown activity in renal cell carcinoma (RCC) and mantel cell lymphoma and is approved as first line treatment in advanced RCC with poor prognostic factors. This review focuses on the clinical use of temsirolimus in RCC, its safety and possible mechanisms of resistance. Keywords: renal cell carcinoma; mTOR inhibitors; efficacy; safety. Received: May 18, 2014; Accepted: July 28, 2014; Published: April 9, 2015 Corresponding Author: Michael Vickers MD, MPH, FRCPC, Medical Oncologist, The Ottawa Hospital Cancer Center, 501 Smyth Road, Ottawa, ON, Canada, K1H 8L6. E-mail: mvickers@toh.on.ca .

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.253
Teacher spread0.228 · 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
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

Citations0
Published2015
Admission routes1
Has abstractyes

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