Bibliographic record
Abstract
The Apgar score is a standardized tool for evaluating newborns in the delivery room. Despite its long history and widespread use, debate remains over its reliability of predicting neonatal outcomes, especially in extremely low-birth-weight premature infants. The aim of the study was to examine the relationship between the 5-minute Apgar score of extremely low-birth-weight infants, as it relates to survival and morbidities associated with prematurity and length of hospital stay. A retrospective query of the Alere neonatal database from 2001 to 2011 examined all infants less than 32 weeks' gestation and less than 1000-g birth weight. The 5-minute Apgar score was divided into 2 groups, score of 4 or greater or less than 4. The study compared results of the 5-minute Apgar score and associated morbidities in surviving infants. Statistical analyses included chi-square, Fisher exact test, t test, and multivariate regression. The sample consisted of 3898 infants with an 86.4% (n = 3366) survival rate. Controlling for gestational age and birth weight, surviving infants with a 5-minute Apgar score of less than 4 were more likely to demonstrate nonintact survival. Infants with a low 5-minute Apgar score have greater risk for mortality and morbidities associated with prematurity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".