MétaCan
Menu
Back to cohort
Record W1499125455 · doi:10.1002/dmrr.2587

Is metformin ready for prime time in pregnancy? Probably not <i>yet</i>

2014· article· en· W1499125455 on OpenAlexafffund
I. George Fantus

Bibliographic record

VenueDiabetes/Metabolism Research and Reviews · 2014
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
FundersCanadian Institutes of Health Research
KeywordsMetforminAMPKPregnancyMedicineType 2 diabetesDiabetes mellitusEndocrinologyInternal medicineOffspringAMP-activated protein kinaseGestational diabetesProtein kinase ABioinformaticsGestationKinaseBiology

Abstract

fetched live from OpenAlex

Metformin is one of the most commonly used drugs to treat type 2 diabetes and is safe and effective. Its main mechanism of action is thought to be the activation of AMP-activated protein kinase (AMPK) via inhibition of mitochondrial ATP generation. Recent use of metformin as an 'insulin sensitizer' in women with polycystic ovarian syndrome to increase fertility has been successful and resulted in the chance observation that continued use during pregnancy appeared to be safe. There are few studies of metformin in animal models of diabetic pregnancy. However, some data have implicated fetal AMPK activation in neural tube defects. While a recent report suggests that metformin may not activate fetal AMPK, which is reassuring, studies in pregnant woman with gestational diabetes and type 2 diabetes, which are ongoing, require completion before we can conclude that its use in pregnancy is safe. Furthermore, follow-up of the offspring will be critical to determine whether such treatment decreases or increases the development of obesity and diabetes.

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)0.002
metaresearch head score (Gemma)0.011
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0100.003

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 head0.112
GPT teacher head0.394
Teacher spread0.282 · 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
GenreCommentary

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

Citations6
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueDiabetes/Metabolism Research and ReviewsSame topicGestational Diabetes Research and ManagementFrench-language works237,207