MétaCan
Menu
Back to cohort
Record W4400930209 · doi:10.3389/fcvm.2024.1426593

Advanced magnetic resonance imaging in human placenta: insights into fetal growth restriction and congenital heart disease

2024· review· en· W4400930209 on OpenAlexaff
Eric Sadiku, Liqun Sun, Christopher K. Macgowan, Mike Seed, Janna L. Morrison

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsPlacentaMagnetic resonance imagingMedicineFetusDiseaseHeart diseaseFetal growthPlacental insufficiencyPregnancyBioinformaticsPathologyRadiologyBiology

Abstract

fetched live from OpenAlex

Placental function plays a crucial role in fetal development, as it serves as the primary interface for delivery of nutrients and oxygen from the mother to fetus. Magnetic resonance imaging (MRI) has significantly improved our ability to visualize and understand the placenta's complex structure and function. This review provides an up-to-date examination of the most common and novel placental MRI techniques. It will also discuss the clinical applications of MRI in diagnosing and monitoring placental insufficiency, as well as its implications for fetal growth restriction (FGR) and congenital heart disease (CHD). Ongoing research using multi-parametric MRI techniques aims to develop novel biomarkers and uncover the relationships between placental parameters and pre-onset diseased states, ultimately contributing to better maternal and fetal health outcomes, which is essential to better guide clinical judgement.

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)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Cardiovascular MedicineSame topicPregnancy and preeclampsia studiesFrench-language works237,207