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Record W4394920460 · doi:10.1111/ajo.13823

The first International Association of Diabetes and Pregnancy Study Groups summit on the diagnosis of gestational diabetes in early pregnancy: <scp>TOBOGM</scp> Summit Report

2024· article· en· W4394920460 on OpenAlexaboutno aff
Arianne Sweeting, Freya MacMillan, David Simmons

Bibliographic record

VenueAustralian and New Zealand Journal of Obstetrics and Gynaecology · 2024
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersUniversity of Sydney
KeywordsGestational diabetesSummitMedicinePregnancyDiabetes mellitusObstetricsGestationScope (computer science)Endocrinology

Abstract

fetched live from OpenAlex

The first International Association of Diabetes and Pregnancy Study Groups Summit on the diagnosis of gestational diabetes in early pregnancy (Treatment of Booking Gestational Diabetes Mellitus (TOBOGM) Summit) was held on the 17 November 2022 in Sydney, Australia. It sought to use the TOBOGM trial findings to scope the issues involved with early screening, to inform future discussions over possible approaches for diagnosing gestational diabetes mellitus (GDM) in early pregnancy. Most delegates supported testing for early GDM using a one-step 75 g oral glucose tolerance test approach with Canadian Diabetes Association criteria preferred, but highlighted the importance of considering resources, cost, consumer perspectives and equity in translating TOBOGM results into a clinical approach to screening for, and diagnosing, early GDM.

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)0.045
metaresearch head score (Gemma)0.045
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0110.004

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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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
GenreOther

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

Citations18
Published2024
Admission routes1
Has abstractyes

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