Optimal birth weight percentile cut‐offs in defining small‐ or large‐for‐gestational‐age
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: It remains questionable what birth weight for gestational age percentile cut-offs should be used in defining clinically important poor or excessive foetal growth. We aimed to evaluate the optimal birth weight percentile cut-offs for defining small- or large-for-gestational-age (SGA or LGA). METHODS: In a birth cohort-based analysis of 17 979 120 non-malformation singleton live births, U.S. 1995-2001, we assessed the optimal birth weight percentile cut-offs for defining SGA and LGA. The 25th-75th percentile group served as the reference. Primary outcomes are the risk ratios (RR) of neonatal death and low 5-min Apgar score (<4) comparing SGA or LGA versus the reference group. More than 2-fold risk elevations were considered clinically significant. RESULTS: The 15th birth weight cut-off already identified SGA infants at more than 2-fold risk of neonatal death at pre-term, term or post-term, except for extremely pre-term births <28 weeks (continuous risk reductions over increasing birth weight percentiles). LGA was associated with a reduced risk of low 5-min Apgar score at pre-term, but an elevated risk at term and post-term. The 97th cut-off identified LGA infants at 2-fold risk of low 5-min Apgar at term. CONCLUSION: The commonly used 10th and 90th birth weight percentile cut-offs for defining SGA and LGA respectively seem largely arbitrary. The 15th and 97th percentiles may be the optimal cut-offs to define SGA and LGA respectively.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it