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Record W2755051026 · doi:10.14341/probl2017633204-207

Molecular genetic aspects of gestational diabetes

2017· article· en· W2755051026 on OpenAlexaff
Vladimir S. Pakin

Bibliographic record

VenueProblems of Endocrinology · 2017
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcGill-Queen's University Press
Fundersnot available
KeywordsGestational diabetesMedicineCandidate geneDiabetes mellitusBioinformaticsGenetic predispositionPreeclampsiaEpigeneticsPregnancyGeneGeneticsBiologyEndocrinologyGestation

Abstract

fetched live from OpenAlex

The incidence of gestational diabetes mellitus (GDM) is currently dramatically increasing throughout the world. The relevant studies of origin and pathogenesis of GDM are of great clinical and scientific value taking into account the intimate association of GDM with serious perinatal complications, including preeclampsia, preterm labor, fetal macrosomia, as well as long-term effects such as the high risk of metabolic syndrome and type 2 diabetes mellitus (T2DM). The pathogenic mechanisms of GDM are rather similar to those of other diabetes, especially T2DM, thus suggesting that GDM is a common multifactorial disorder involving numerous genetic and provocative exogenous factors. The data in favor of inherited predisposition to GDM are briefly discussed and a short overview of the known GDM candidate genes is given. According to present knowledge, the gene network of GDM includes dozens of genes and is rather similar to that in GDM. The features of gene network associated with GDM and the ones known for other types of DM are outlined. Special attention is given to the known GDM biomarkers, which are especially important for understanding of the molecular genetic and epigenetic mechanisms of GDM development, its early predictive diagnosis, efficient prevention and personalized treatment.

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 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.023
GPT teacher head0.300
Teacher spread0.277 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations4
Published2017
Admission routes1
Has abstractyes

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