Bibliographic record
Abstract
Introduction In most jurisdictions an infant is regarded as premature when delivered at fewer than 37 weeks gestation [1,2]. The proportion of babies born prematurely rather than at term is small: 18% in the United States in 2009 [3], 12% in England and Wales [4], and 7.4% in Australia [5]. But the risks to a pre-term infant are significant and those risks increase with greater prematurity. In England, Wales, and Northern Ireland, there is nearly one neonatal death per 1000 live births at term, but this rises to 204 deaths per 1000 births in babies born between 24 and 27 weeks gestation [6]. Further, especially in this latter very pre-term group, survivors display significant morbidity, including chronic respiratory disease, ultrasound-detected brain injury, and retinopathy of prematurity [7]. While there is evidence of a reducing mortality in most pre-term gestations, there are some indications that this is at the expense of increased morbidity [8]. Even late pre-term babies have a higher risk of morbidity, particularly respiratory problems and infectious diseases, than term infants [9]. Premature birth is spontaneous and without a specific recognized cause in some 31–51% of cases, but there is an increased risk associated with multiple pregnancy (12–28%), premature membrane rupture (6–40%), cervical incompetence (8–9%), and antepartum hemorrhage (6–9%). Associated ascending infection may be a significant factor in some of these conditions [10]. An obstetric decision to deliver early may be influenced by a number of additional factors, such as fetal growth restriction and maternal hypertension.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".