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Metformin and Hepatic Carcinogenesis

2012· letter· en· W2116073185 on OpenAlex
Michaël Pollak, Ana M. González-Angulo

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.

Bibliographic record

VenueCancer Prevention Research · 2012
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcGill University
Fundersnot available
KeywordsMetforminMedicineCancerCarcinogenesisOncologyClinical trialInternal medicinePopulationMechanism (biology)CarcinogenBioinformaticsPharmacologyEnvironmental healthBiologyInsulin

Abstract

fetched live from OpenAlex

Retrospective, hypothesis-generating population studies suggest that diabetics treated with metformin have a substantially reduced risk of several cancers, including hepatoma, relative to diabetics on other therapies. In this issue of the journal (beginning on page 544), Bhalla and colleagues contribute to the growing literature on metformin effects in experimental carcinogenesis models, showing reduced carcinogen-induced hepatoma in mice. The clinical need to develop novel prevention strategies for hepatoma is obvious, given an increasing prevalence and poor prognosis. The clues that metformin or related biguanides may have utility in this area justify accelerated laboratory research, as more data concerning mechanism, pharmacokinetics, and predictors of efficacy will help to optimize the design of clinical trials.

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)0.001
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.241
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.083
GPT teacher head0.395
Teacher spread0.312 · 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