Prenatal diagnosis and risk stratification of congenital diaphragmatic hernia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Congenital diaphragmatic hernia (CDH) is a rare heterogenous disorder with varying degrees of severity. Infant survival rates in high-income countries are approaching 80% in isolated CDH; however, over 50% will have long-term morbidities. Advanced antenatal imaging, including ultrasound and magnetic resonance imaging, has made it possible to prognosticate severity of CDH and to stratify risk when counseling expectant parents. Risk stratification can also better prepare healthcare teams to enable optimal neonatal management, and provide options for fetal intervention or, where legally permitted, pregnancy termination. Factors that may affect the immediate and long-term prognosis for CDH include prenatal diagnosis, gestational age at detection and delivery, side of the defect, presence of additional structural or genetic abnormalities, defect size, estimation of fetal lung volume, the extent of visceral herniation, and the delivery center's experience in caring for neonates with CDH. Optimizing the outcome for families and infants begins with an early prenatal diagnosis followed by referral to a diverse and inclusive multidisciplinary center with CDH expertise. Prediction of disease severity is supported by accurate fetal imaging and comprehensive genetic testing, and allows the care team to provide realistic outcome expectations during the counseling of expectant parents of all racial and ethnic backgrounds.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it