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Umbilical Artery Eucapnic pH to Assess Fetal Well-being

2025· article· en· W4410947895 on OpenAlexaff
Thierry Daboval, P Ouellet, Amr El Shahed, Linh Ly, Caroline Ahearne, C Racinet

Bibliographic record

VenueObstetric Anesthesia Digest · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineUmbilical arteryFetusAnesthesiaCardiologyAnimal scienceInternal medicinePregnancyBiology

Abstract

fetched live from OpenAlex

(Am J Obstet Gynecol. 2024;231(3):348.e1-8. doi: 10.1016/j.ajog.2024.03.042) This study aimed to compare the effectiveness of different biomarkers—umbilical artery pH (Ua pH), base deficit (BD), and neonatal eucapnic pH (pH euc-n)—in predicting hypoxic-ischemic encephalopathy (HIE) in newborns. The primary goal was to determine which marker offers the best ability to identify newborns at risk for brain injury, specifically those who might benefit from therapeutic hypothermia. Therapeutic hypothermia, a treatment for moderate-to-severe HIE, relies on early identification of the condition, typically through assessments of fetal acid-base balance through biomarkers in cord blood and clinical assessment.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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
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
Published2025
Admission routes1
Has abstractyes

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