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Time Trends in Preeclampsia and Gestational Diabetes in Denmark and Alberta, Canada, 2005 to 2018: A Population-Based Cohort Study

2024· article· en· W4404518210 on OpenAlexaboutno aff
Frederikke Lihme, A. Savu, Saima Basit, Winnie Sia, Roseanne O. Yeung, O. Barrett, Laila Luoma, Deliwe P. Ngwezi, S. Davidge, Colleen M. Norris, Maria B. Ospina, Christy‐Lynn M. Cooke, Russell Greiner, Jan Wohlfahrt, Mads Melbye, Jacob Alexander Lykke, P. Kaul, H.A. Boyd

Bibliographic record

VenueObstetric Anesthesia Digest · 2024
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGestational diabetesPreeclampsiaObstetricsCohortPopulationDemographyPregnancyGestationEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

(Acta Obstet Gynecol Scand. 2024;103:266–275. doi: 10.1111/aogs.14703) Preeclampsia (PEC) and gestational diabetes mellitus (GDM) have similar risk factors including increased maternal age and obesity. Both conditions are associated with adverse pregnancy outcomes and long-term health issues for mothers and children, and health care resources could be strained if the prevalence of PEC and GMA are increasing.

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)0.002
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 score0.019
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.234
Teacher spread0.225 · 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
Published2024
Admission routes1
Has abstractyes

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