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Record W2343591155 · doi:10.4103/2347-5625.178174

Meeting An Unmet Need in Metastatic Colorectal Carcinoma with Regorafenib

2016· review· en· W2343591155 on OpenAlexaff
Barbara Melosky

Bibliographic record

VenueAsia-Pacific Journal of Oncology Nursing · 2016
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsRegorafenibMedicineColorectal cancerClinical trialIntensive care medicineMultidisciplinary approachOncologyRandomized controlled trialDiseaseInternal medicineCancer

Abstract

fetched live from OpenAlex

Colorectal cancer is a global issue, affecting men and women equally. Over the last 25 years, advances in therapy and multidisciplinary care have led to improvements in survival for those with colorectal cancer. Despite these advances, more therapeutic options are needed for those being treated for this disease. Regorafenib is an oral drug that is a new therapeutic option for our patients. The CORRECT and CONCUR trials demonstrate the efficacy of regorafenib in the last line setting. This article summarizes some of the regorafenib clinical trial data and discusses the strategies to help manage the side effects of this drug including patient education, dose reductions and interruptions, and monitoring hypertension and liver function.

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)0.002
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.052
GPT teacher head0.386
Teacher spread0.334 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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Same venueAsia-Pacific Journal of Oncology NursingSame topicColorectal Cancer Treatments and StudiesFrench-language works237,207