MétaCan
Menu
Back to cohort
Record W1988782755 · doi:10.3322/caac.20078

Diabetes and Cancer: A Consensus Report

2010· article· en· W1988782755 on OpenAlexaff
Edward L. Giovannucci, David M. Harlan, Michael C. Archer, Richard M. Bergenstal, Susan M. Gapstur, Laurel A. Habel, Michaël Pollak, Judith G. Regensteiner, Douglas Yee

Bibliographic record

VenueCA A Cancer Journal for Clinicians · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsDiabetes mellitusMedicineCancerIncidence (geometry)Cancer incidenceGerontologyFamily medicineIntensive care medicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Epidemiologic evidence suggests that cancer incidence is associated with diabetes as well as certain diabetes risk factors and treatments. This consensus statement of experts assembled jointly by the American Diabetes Association and the American Cancer Society reviews the state of science concerning 1) the association between diabetes and cancer incidence or prognosis; 2) risk factors common to both diabetes and cancer; 3) possible biologic links between diabetes and cancer risk; and 4) whether diabetes treatments influence the risk of cancer or cancer prognosis. In addition, key unanswered questions for future research are posed.

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)0.026
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0050.005
Research integrity0.0110.012
Insufficient payload (model declined to judge)0.0070.005

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 head0.019
GPT teacher head0.348
Teacher spread0.328 · 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

Citations1,062
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCA A Cancer Journal for CliniciansSame topicMetabolism, Diabetes, and CancerFrench-language works237,207