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Record W2086847261 · doi:10.1111/aogs.12076

Does multi‐fetal pregnancy reduction adversely influence intra‐uterine growth?

2012· article· en· W2086847261 on OpenAlexaff
Richard Brown, Alon Shrim, Angela Mallozzi

Bibliographic record

VenueActa Obstetricia Et Gynecologica Scandinavica · 2012
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineGestationPregnancyObstetricsFetusIn uteroTwin PregnancyGestational ageGynecologyBiology

Abstract

fetched live from OpenAlex

Multi-fetal pregnancy reduction (MFPR) is offered in the management of higher-order multiple gestations to reduce the risks associated with such pregnancies. Pregnancy outcomes, including birthweight, following MFPR have been examined with variable findings. However, little attention has been paid to in utero growth in such pregnancies. This study examines whether the intra-uterine growth performance of a twin pregnancy resulting from MFPR differs from that of an unreduced twin pregnancy. This was a retrospective analysis comparing the intrauterine growth of 20 higher order multiple pregnancies that underwent MFPR with resulting di-chorionic twin gestations with 293 unreduced di-chorionic twin gestations. Biometric nomograms were derived for the unreduced twin population and the biometric parameters for the reduced pregnancies were compared with these. There was a difference with respect to femur length in the period 20-28 weeks (p = 0.003) but no other significant differences were observed. MFPR does not itself adversely influence intra-uterine fetal growth.

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)0.005
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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)0.0010.000

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 head0.026
GPT teacher head0.298
Teacher spread0.272 · 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
Published2012
Admission routes1
Has abstractyes

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