Split‐week gestational age model provides valuable information on outcomes in extremely preterm infants
Bibliographic record
Abstract
AIM: To compare composite outcomes of neonatal mortality or morbidity using a split-week gestational age (GA) model to completed weeks GA maturity at 23-26 weeks gestation. METHODS: This was a retrospective cohort study of infants born at 23-26 weeks GA. Outcomes using a split-week GA model defined as early (X, 0-3) and late (X, 4-6) with X being 23-26 weeks GA were compared to outcomes using completed weeks GA, with a similar comparison between the late split of the preceding week (X, 4-6) and early split of the subsequent week (X + 1, 0-3). RESULTS: A total of 1345 infants were included in the study. Statistically significant differences were noted in outcomes between the early and late split of the gestational week at 24 (early vs late, 85.6% vs 73.0%), 25 (69.6% vs 56.6%) and 26 weeks (55.9% vs 37.4%), but not at 23 weeks GA (95.2% vs 94.5%). No statistically significant differences were noted between the late vs early part of the subsequent week (23, 4-6) vs (24, 0-3), and (24, 4-6) vs (25, 0-3) GA. CONCLUSION: Neonatal outcome estimates using a split week model differs from that based on the use of completed weeks of gestational maturity.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".