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Record W2776110744 · doi:10.1111/echo.13760

New advances in fetal cardiovascular magnetic resonance imaging for quantifying the distribution of blood flow and oxygen transport: Potential applications in fetal cardiovascular disease diagnosis and therapy

2017· review· en· W2776110744 on OpenAlex
Liqun Sun, Christopher K. Macgowan, Sharon Portnoy, John G. Sled, Shi‐Joon Yoo, Lars Grosse‐Wortmann, Edgar Jaeggi, John‏ Kingdom, Mike Seed

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEchocardiography · 2017
Typereview
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsMount Sinai HospitalSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsFetusFetal circulationOxygen transportMedicineBlood flowCirculatory systemCardiologyMagnetic resonance imagingDiseaseHemodynamicsInternal medicineDistribution (mathematics)PregnancyRadiologyOxygenBiologyPlacentaChemistry

Abstract

fetched live from OpenAlex

Until recently, our modern understanding of fetal circulatory physiology has been largely based on invasive measurements made in fetal sheep. However, new MRI technology developed by our group has provided equivalent information about the distribution of blood flow and oxygen transport noninvasively. The initial findings largely confirm prior estimates about the human fetal circulation extrapolated from fetal sheep data and human ultrasound data. Here we describe the hemodynamics of the normal late gestation human fetal circulation by MRI and speculate about what the advent of this technology might mean in terms of the management of fetuses affected by placental insufficiency and congenital heart disease.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.284
Teacher spread0.254 · 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