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Record W2793498399 · doi:10.1159/000485157

Pregnancy and End-Stage Renal Disease

2018· review· en· W2793498399 on OpenAlexaff
Jessica Sheehan Tangren, Molly Nadel, Michelle Hladunewich

Bibliographic record

VenueBlood Purification · 2018
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePregnancyDialysisEnd stage renal diseaseIntensive care medicineObstetricsFertilityDiseasePeritoneal dialysisSurgeryPopulationInternal medicine

Abstract

fetched live from OpenAlex

Pregnancy is uncommon in women with end-stage renal disease (ESRD). Fertility rates are low in women on dialysis, and physicians still frequently counsel women with ESRD against pregnancy. Advancements in the delivery of dialysis and obstetric care have led to improved live birth rates in women on dialysis, so pregnancy for young women with ESRD is now more feasible and safer. However, these pregnancies remain high-risk for both maternal and fetal complications, necessitating experienced multidisciplinary care. In this article, we review fertility issues in women with ESRD, discuss pregnancy outcomes in women on dialysis, and provide an approach for management of pregnant women with ESRD.

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)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.064
GPT teacher head0.352
Teacher spread0.288 · 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
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

Citations78
Published2018
Admission routes1
Has abstractyes

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