The current state of birth outcome and birth defect surveillance in northern regions of the world
Bibliographic record
Abstract
OBJECTIVES: Little is known about the rates of congenital anomalies in the northernmost regions of the world. As in other parts of the world, it is crucial to assess the relative rates and trends of adverse birth outcomes and birth defects, as indicators of population health and to develop public health strategies for prevention. The aim of this review is to catalogue existing and developing birth outcome and birth defect surveillance within and around the geographic jurisdiction of the International Union of Circumpolar Health (IUCH). STUDY DESIGN: Descriptive study. METHODS: The representatives of the IUCH Birth Defects Working Group catalogued existing and developing birth and birth defect surveillance systems and the extent of information they contain to determine inter-regional comparability. RESULTS: Systematic population-based registration of birth outcomes including birth defects occurs to some degree in all circumpolar countries, but the quality of collection and the coverage in northernmost regions vary. There are limited circumpolar jurisdictions with surveillance systems collecting birth defect information beyond the perinatal period. Efforts are underway in Canada and Russia to improve the quality and comprehensiveness of the information collected in the northern regions. CONCLUSIONS: Although there is variability in the comprehensiveness of information collected in northern jurisdictions limiting sophisticated comparative analyses between regions, there is untapped potential for baseline analyses of specific risks and outcomes that could provide insight into geographic differences and gaps in surveillance that could be improved.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".