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Record W2625717818 · doi:10.1097/ogx.0000000000000452

The Limits of Electronic Fetal Heart Rate Monitoring in the Prevention of Neonatal Metabolic Acidemia

2017· article· en· W2625717818 on OpenAlexaff
Steven L. Clark, Emily Hamilton, Thomas J. Garite, Audra Timmins, Philip Warrick, Samuel Smith

Bibliographic record

VenueObstetrical & Gynecological Survey · 2017
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMcGill UniversityCanadian Institute of Mining, Metallurgy and Petroleum
Fundersnot available
KeywordsMedicineFetal heart rateFetusHeart rateElectronic fetal monitoringHypoxia (environmental)Metabolic rateIntensive care medicineCardiologyInternal medicinePregnancyBlood pressure

Abstract

fetched live from OpenAlex

(Abstracted from Am J Obstet Gynecol 2017;216:163.e1–163.e6) Despite advances in technology and training, averting the neurologic injury causing hypoxia-induced fetal metabolic acidemia has not been demonstrated. By examining fetal heart rate tracings of infants with base deficit of more than 12 and base deficit of less than 8, this study seeks to assess the validity of electronic fetal heart rate monitoring (EFM) in preventing adverse metabolic acidemia–related outcomes and validate a fetal heart rate interpretation algorithm, specifically designed to assist with the management of category II fetal heart rate tracings.

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)0.026
metaresearch head score (Gemma)0.114
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.114
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.340
Teacher spread0.279 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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