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Record W4394785719 · doi:10.1002/pd.6571

Fetal cardiac screening: 1st trimester and beyond

2024· review· en· W4394785719 on OpenAlexaff
Lindsay R. Freud, Lynn L. Simpson

Bibliographic record

VenuePrenatal Diagnosis · 2024
Typereview
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineFetusPregnancyPrenatal diagnosisObstetricsPrenatal screeningSecond trimesterPediatrics

Abstract

fetched live from OpenAlex

Congenital heart defects (CHD) are the most common birth defect and a leading cause of infant morbidity and mortality. CHD often occurs in low-risk pregnant patients, which underscores the importance of routine fetal cardiac screening at the time of the 2nd trimester ultrasound. Prenatal diagnosis of CHD is important for counseling and decision-making, focused diagnostic testing, and optimal perinatal and delivery management. As a result, prenatal diagnosis has led to improved neonatal and infant outcomes. Updated fetal cardiac screening guidelines, coupled with technological advancements and educational efforts, have resulted in increased prenatal detection of CHD in both low- and high-risk populations. However, room for improvement remains. In recent years, fetal cardiac screening for specific high-risk populations has started in the 1st trimester, which is a trend that is likely to expand over time. This review discusses fetal cardiac screening throughout pregnancy.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.050
GPT teacher head0.351
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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