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Do Labetalol and Methyldopa Have Different Effects on Pregnancy Outcome? Analysis of Data From the Control of Hypertension In Pregnancy Study (CHIPS) Trial

2017· article· en· W2615199480 on OpenAlexaff
Laura A. Magee, Joel Singer, T. Lee, É. Rey, Susan M. Ross, E Asztalos, Karen E. Murphy, Jennifer Menzies, Judith Sanchez, Amiram Gafni, Andrée Gruslin, Michael Helewa, Eileen K. Hutton, Gideon Koren, S.K. Lee, A G Logan, Wessel Ganzevoort, Ross Welch, Jim Thornton, J.-M. Moutquin

Bibliographic record

VenueObstetric Anesthesia Digest · 2017
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLabetalolMedicineMethyldopaPregnancyObstetricsBlood pressureGestational hypertensionFirst trimesterGestationInternal medicine

Abstract

fetched live from OpenAlex

(BJOG. 2016;123:1143–1151) The Control of Hypertension In Pregnancy Study (CHIPS trial) investigated the impact of a target blood pressure (BP) on maternal and perinatal outcomes by randomizing women with gestational or preexisting hypertension to a diastolic BP target of 100 (“less tight” control group) versus 85 mm Hg (“tight” control group). The present study, a secondary analysis of the CHIPS trial data, aimed to compare pregnancy outcomes between women taking methyldopa or labetalol while considering the allocation of these patients to the “less tight” or “tight” control group.

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)0.011
metaresearch head score (Gemma)0.024
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.324
Teacher spread0.227 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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