Symphysis fundal height charts: Results from the Brazilian Maternal and Child Nutrition Consortium
Bibliographic record
Abstract
OBJECTIVES: To construct prescriptive symphysis fundal height (SFH) curves based on data from the Brazilian Maternal and Child Nutrition Consortium (BMCNC). METHODS: Individual patient data from seven cohorts from the BMCNC were used. Adult women with singleton pregnancies, free of infectious and chronic diseases, gestational diabetes, and hypertensive disorders, who did not smoke or consume alcohol during pregnancy and delivered a live birth at term, adequate for gestational age, and with birth weight between 2500 and 4000 g were selected. SFH was obtained from medical records. The data were harmonized and cleaned and then split into training (n = 3969 individuals; 21 760 SFH measurements) and validation (n = 1700 individuals; 9284 SFH measurements). Fractional polynomial models were used to construct SFH curves between 14 and 40 gestational weeks. RESULTS: The predicted median for SFH at 40 weeks was 36.1 cm (interquartile range, 34.5-37.7 cm). The internal and cross-validation results showed that the percentages of SFH measurements below the selected percentiles were close to those expected. CONCLUSION: The new SFH charts will allow healthcare professionals to monitor SFH and identify individuals at risk for delivering neonates with adverse outcomes, improving the prenatal care routine in Brazil.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".