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Record W2142036989 · doi:10.1080/15227950590961171

COMPARISON OF FETAL BEHAVIOR IN LOW- AND HIGH-RISK PREGNANCIES

2005· review· en· W2142036989 on OpenAlexaff
Barbara S. Kisilevsky, Sylvia M. J. Hains

Bibliographic record

VenueFetal and Pediatric Pathology · 2005
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsMedicineFetusNonstress testGestationPregnancyObstetricsFetal heart rateInternal medicineBlood pressureHeart rate

Abstract

fetched live from OpenAlex

Meta-analyses were conducted on archival data of human fetal behavior to identify differential behavior among high-risk fetuses in pregnancies complicated by threatened preterm delivery, maternal hypertension or diabetes compared with low-risk fetuses in uneventful pregnancies, delivering as healthy, full-term infants. Data for a total of 493 fetuses (260 high risk, 233 low risk) from 23 weeks' gestation to term who participated in a study using a standardized protocol including observations of spontaneous and auditory-induced behavior were retrieved from our laboratory database. There were no differences in spontaneous behaviors when scored using clinical criteria for the nonstress test and biophysical profile; however, there were differences in the magnitude of the behaviors measured in the tests. Developmental differences were observed between those threatening to deliver early and the fetuses of hypertensive and diabetic mothers. The latter two groups differed little from one another but differed from low-risk fetuses in their response to auditory stimulation. We concluded that differences in behavior among high-risk groups suggest that atypical fetal behaviors may represent adaptation to condition specific insult rather than a generalized response to insult per se. The finding that high-risk fetuses showed atypical responses to auditory stimuli indicates a need to examine the relation between fetal auditory function and later language acquisition.

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 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)0.000
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 score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.335
Teacher spread0.300 · 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 teacher head, not a consensus.

Study designOther design
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

Citations13
Published2005
Admission routes1
Has abstractyes

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