The association between glucose challenge test level and fetal nutritional status
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between maternal glucose challenge test (GCT) levels and fetal nutritional status index (FNSI: a ratio of child's birth weight (kg) over squared maternal height (m(2)). METHODS: A total of 2193 women from the Beichen district, Tianjin, China, who had 50 g GCT at gestational age 24-28 weeks, gave a full-term singleton birth between June 2011 and October 2012, and with both maternal height and birth weight measures are included in this report. RESULTS: Approximately 28.0% of women had a GCT ≥ 7.8 mmol/L. The newborns of mothers with a GCT ≥ 7.8 mmol/L had significantly higher level of FNSI ([kg/m(2)], boys: 1.336 versus 1.296, p < 0.001; girls: 1.312 versus 1.268, p < 0.0001). Logistic regression results, after adjustment for maternal age, residence, education, nationality, history of disease and reproduction, insurance and gestational age, indicated that every unit increase in FNSI was associated with approximately threefold higher odds (OR [95% CI]: 3.6 [1.5, 8.9]) of being in GCT ≥ 7.8 mmol/L for women giving birth as boys and fivefold higher odds (5.9 [2.5, 14.1]) for giving birth as girls. CONCLUSIONS: Women with a GCT ≥ 7.8 mmol/L have babies with a higher FNSI, suggesting that these infants may be overnourished before birth and may increase cardiovascular risk in their future.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".