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Metformin in Cancer Treatment and Prevention

2014· review· en· W2136386001 on OpenAlexaff
Daniel R. Morales, Andrew D. Morris

Bibliographic record

VenueAnnual Review of Medicine · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsMetforminMedicineCancerDiabetes mellitusType 2 Diabetes MellitusPharmacologyOncologyInternal medicineBioinformaticsEndocrinologyBiology

Abstract

fetched live from OpenAlex

Patients with diabetes mellitus are at increased risk of cancer development. Metformin is a well-established, effective agent for the management of type 2 diabetes mellitus. Epidemiological studies have identified an association between metformin use and a beneficial effect on cancer prevention and treatment, which has led to increasing interest in the potential use of metformin as an anticancer agent. Basic science has provided a better understanding of the mechanism of action of metformin and the potential for metformin to modulate molecular pathways involved in cancer cell signaling and metabolism. This article outlines the link between metformin and cancer, the potential for metformin in oncology, and limitations of currently available evidence.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.033
GPT teacher head0.407
Teacher spread0.374 · 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

Citations485
Published2014
Admission routes1
Has abstractyes

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