Public health priorities for gastroschisis: Summary of a meeting sponsored by the Centers for Disease Control and Prevention and the March of Dimes
Bibliographic record
Abstract
BACKGROUND: Gastroschisis has increased worldwide over several decades; however, there are significant gaps in understanding risk factors for development of the defect, particularly those that might be modifiable. Despite advances in survival, little is known about longer-term outcomes for affected individuals. METHODS: On April 27- and 28, 2023, the National Center on Birth Defects and Developmental Disabilities at the Centers for Disease Control and Prevention (CDC) and March of Dimes sponsored a meeting entitled "Public Health Priorities for Gastroschisis". The meeting goals were to review current knowledge on gastroschisis, discuss research gaps, and identify future priorities for public health surveillance, research, and action related to gastroschisis. Meeting participants encompassed a broad range of expertise and experience, including public health, clinical care of individuals with gastroschisis, affected individuals and families, and representatives from professional organizations and federal agencies. RESULTS: Several goals were identified for future public health surveillance and research, including focused theory-driven research on risk factors and increased study of longer-term effects of gastroschisis through improved surveillance. Certain public health actions were identified, that which could improve the care of affected individuals, including increased education of providers and enhanced resources for patients and families. CONCLUSIONS: These efforts may lead to an improved understanding of pathogenesis, risk factors, and outcomes and to improved care throughout the lifespan.
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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 | 0.024 | 0.014 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".