Predicting the metabolic future of children using fetal glycated hemoglobin, anovel biomarker
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".