Factors determining admission to neonatal units in Jamaica
Bibliographic record
Abstract
In order to identify the factors associated with admission to neonatal care units in a developing country, 1,823 newborns admitted to Jamaica's eight neonatal care units over a 6-month period were compared with 9,563 newborns identified during an island-wide population morbidity study. Maternal sociodemographic characteristics, past obstetric history, infant's growth parameters at birth and mode and place of delivery were investigated. Babies of mothers resident in the two regions of the island where specialist paediatric services were available had increased odds of admission (OR= 1.45, 1.22) compared with those living elsewhere (OR=0.70, 0.80). Maternal history of a previous miscarriage, termination or early neonatal death were associated with subsequent admission, but a previous stillbirth or late neonatal death were not. Very low birthweight infants of gestational age 28-31 weeks were more likely to be admitted than those < 28 weeks with ORs of 1.45 and 0.34 respectively. Factors determining neonatal admission in the developing world may be quite different from those of developed countries. The development of guidelines and support services to ensure wider access to these services for those most in need could contribute to more equitable utilisation of services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".