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Metformin and Other Biguanides in Oncology: Advancing the Research Agenda

2010· review· en· W2165189414 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCancer Prevention Research · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Cancer Society Research InstituteNational Cancer InstituteProstate Cancer FoundationNational Institutes of HealthProstate Cancer CanadaMcGill University
KeywordsMetforminMedicineCancerDiabetes mellitusClinical trialOncologyInternal medicineClinical OncologyIntensive care medicinePharmacologyBioinformaticsEndocrinology

Abstract

fetched live from OpenAlex

Retrospective studies that may be impractical to confirm prospectively suggest that diabetics treated with metformin have a substantially reduced cancer burden compared with other diabetics. It is unclear if this reflects a chemopreventive effect, an effect on transformed cells, or both. It also remains to be established if these data have relevance to people without diabetes. Laboratory models, however, provide independent impressive evidence for the activity of metformin and other biguanides in both cancer treatment and chemoprevention. Investigations of mechanisms of action of biguanides have revealed considerable complexity and have identified important gaps in knowledge that should be addressed to ensure the optimal design of clinical trials of these agents. Such trials may define important new indications for biguanides in the prevention and/or treatment of many common cancers.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.991
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.287
GPT teacher head0.562
Teacher spread0.276 · 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