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Record W2530930251

Predicting the metabolic future of children using fetal glycated hemoglobin, anovel biomarker

2015· article· en· W2530930251 on OpenAlex
Jean Luc Ardilouze

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

VenueJournal of Diabetes & Metabolism · 2015
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineGlycated hemoglobinGlycationOffspringGestational diabetesBiomarkerGlycemicFetusCohortInternal medicineHemoglobinCord bloodDiabetes mellitusPregnancyObstetricsEndocrinologyGestationType 2 diabetesBiologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

T lifetime risk of metabolic diseases in offspring of women with gestational diabetesmellitus (GDM) depends, at least in part, on the impact of glycemic fetal programming. To quantify this impact, we have developed and validated a unique mass-spectrometrymethod to measure the percentage of glycated hemoglobin in cord blood. This first casecontrolstudy includes 37 GDM women and 30 pregnant women with normal glucosetolerance (NGT). Glycation of the α-chain (Glα) was higher in neonates from GDM(2.32% vs. 2.20%; P<0.01). Glα strongly correlated with maternal A1c measured atdelivery in the overall cohort (r = 0.67; P<0.0001) as well as in each group (GDM: r =0.66; P<0.0001; NGT: r = 0.50; P=0.01). Thus, Glα may reflect hyperglycemic exposureduring the last weeks of fetal development. Future studies will confirm Glα is a predictivebiomarker of fetally programmed lifetime metabolic health and disease.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.291
Teacher spread0.264 · 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