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Record W2521127922 · doi:10.1002/uog.16028

OC01.03: <sup>*</sup>Relationship between oxygen saturation and blood flow distribution in the late gestation human fetus by <scp>MRI</scp>

2016· article· en· W2521127922 on OpenAlexaff
Paolo Ricci, Meng Yuan Zhu, Flavia Ventriglia, Emanuele Messina, Mike Seed

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2016
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBlood flowMedicineOxygen saturationFetusAscending aortaUmbilical veinHemodynamicsGestationSaturation (graph theory)Inferior vena cavaInternal medicineCardiologyCerebral blood flowAnatomyAortaAnesthesiaOxygenPregnancyBiologyChemistry

Abstract

fetched live from OpenAlex

To identify the relationship between cerebral, pulmonary and umbilical blood flow with arterial oxygen saturations in normal and IUGR fetuses using MRI. Fetal O2 saturation and blood flow in the major vessels were measured using phase-contrast MRI with metric optimised gating and T2 mapping according to our previously published technique. IUGR patients were identified based on a composite score of prenatal Doppler, placental histopathology and neonatal anthropometric indices. Statistical analysis was performed using SPSS to produce fitted models for the correlations between arterial O2 saturation and blood flow. 56 human fetuses (9 IUGR and 47 normal) were studied during late gestation. Cerebral blood flow increased with lower ascending aorta O2 saturation. The figure illustrates the relationships between blood flow in the superior vena cava (SVC flow) with oxygen saturation in the ascending aorta, AAoSaO2 (R = 0.45; P < 0.0001); pulmonary blood flow (PBF) was negatively correlated with oxygen saturation in the main pulmonary artery, MPASaO2 (R = 0.192; P = 0.004); umbilical vein blood flow (UV flow) was inversely proportional to umbilical vein oxygen saturation, UVSaO2 (R = 0.117; P = 0.010). Supporting information can be found in the online version of this abstract Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0520.006

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2016
Admission routes1
Has abstractyes

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