Bibliographic record
Abstract
<b>Objectives</b> To examine variations in the registration of extremely low birthweight and early gestation births and to assess their effect on perinatal and infant mortality rankings of industrialised countries. <b>Design</b> Retrospective population based study. <b>Setting </b>Australia, Canada, European countries, and the United States for 2004; Australia, Canada, and New Zealand for 2007. <b>Population</b> National data on live births and on fetal, neonatal, and infant deaths. <b>Main outcome measures</b> Reported proportions of live births with birth weight/gestational age of less than 500 g, less than 1000 g, less than 24 weeks, and less than 28 weeks; crude rates of fetal, neonatal, and infant mortality; mortality rates calculated after exclusion of births under 500 g, under 1000 g, less than 24 weeks, and less than 28 weeks. <b>Results</b> The proportion of live births under 500 g varied widely from less than 1 per 10 000 live births in Belgium and Ireland to 10.8 per 10 000 live births in Canada and 16.9 in the United States. Neonatal deaths under 500 g, as a proportion of all neonatal deaths, also ranged from less than 1% in countries such as Luxembourg and Malta to 29.6% in Canada and 31.1% in the United States. Rankings of countries based on crude fetal, neonatal, and infant mortality rates differed substantially from rankings based on rates calculated after exclusion of births with a birth weight of less than 1000 g or a gestational age of less than 28 weeks. <b>Conclusions</b> International differences in reported rates of extremely low birthweight and very early gestation births probably reflect variations in registration of births and compromise the validity of international rankings of perinatal and infant mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 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".