Preterm birth: Case definition & guidelines for data collection, analysis, and presentation of immunisation safety data
Bibliographic record
Abstract
Preterm birth is commonly defined as any birth before 37 weeks completed weeks of gestation. An estimated 15 million infants are born preterm globally, disproportionately affecting low and middle income countries (LMIC). It contributes directly to estimated one million neonatal deaths annually and is a significant contributor to childhood morbidity. However, in many clinical settings, the information available to calculate completed weeks of gestation varies widely. Accurate dating of the last menstrual period (LMP), as well as access to clinical and ultrasonographic evaluation are important components of gestational age assessment antenatally. This case definition assign levels of confidence to categorisation of births as preterm, utilising assessment modalities which may be available across different settings. These are designed to enable systematic safety evaluation of vaccine clinical trials and post-implementation programmes of immunisations in pregnancy.
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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 | 0.096 | 0.194 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.028 | 0.022 |
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".