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Record W3035936103 · doi:10.12891/ceog3740.2018

Placental pathology findings and birth weight discordance

2018· article· en· W3035936103 on OpenAlexaff
Shayesteh Jahanfar, Kenneth Lim

Bibliographic record

VenueClinical and Experimental Obstetrics & Gynecology · 2018
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsB.C. Women's Hospital & Health Centre
Fundersnot available
KeywordsPlacentaMedicineObstetricsMonochorionic twinsAnastomosisFetusPregnancyUmbilical cordCohortGestationCordTwin PregnancyPathologicalBirth weightFetal growthRetrospective cohort studyPathologySurgeryAnatomyBiology

Abstract

fetched live from OpenAlex

Purpose: To assess the fetal, perinatal, and maternal outcomes in twin pregnancy according to chorionicity. Materials and Methods: This was a retrospective cohort study of 1,571 twin pregnancies with placental pathological examination collected from 2000-2010. Fetal, neonatal, and maternal outcomes of twins were compared via multivariate analysis. Results: Placenta anastomosis, unequal placenta sharing, cord size, and cord insertion type were found to be the key elements that impacted growth discordance in twin gestations. Higher rates of severe growth discordance were negatively associated with higher frequencies of anastomosis. Placentas in monochorionic twins were more likely to have shared arteries/veins. Discussion: Monochorionic placentas compensate for lack of nutritional flow by penetrating to other placenta surfaces. Compensation for lack of vascular sufficiency would mean a fused placenta or sharing more portions of the placenta. Higher rates of unequal placenta sharing among growth discordant twins is reported irrespective of chorionicity. Conclusion: Attention to placenta pathology is important in growth discordant twins.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.336
Teacher spread0.310 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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