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Record W2961279790 · doi:10.1002/dmrr.3205

Past, present and future of latent autoimmune diabetes in adults

2019· review· en· W2961279790 on OpenAlexaff
Bingwen Liu, Yufei Xiang, Zhenqi Liu, Zhiguang Zhou

Bibliographic record

VenueDiabetes/Metabolism Research and Reviews · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsMinistry of Education and Child Care
FundersNational Science and Technology Infrastructure ProgramInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsAutoimmune diabetesDiabetes mellitusMedicineType 1 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Latent autoimmune diabetes in adults (LADA) is the most common form of autoimmune diabetes diagnosed in adults. Similar to type 1 diabetes, the prevalence of LADA is impacted by ethnicity and geography. LADA is characterized by β cell loss due to autoimmunity and insulin resistance and has highly heterogeneous clinical features, autoimmunity, and genetics in a glutamic acid decarboxylase antibody (GADA) titre-dependent manner, suggesting LADA is part of a continuum spectrum between type 1 and type 2 diabetes. Although LADA is the most frequent form of autoimmune diabetes diagnosed in adults, clinical trials involving LADA are scarce. Here we review the recent advancements in LADA epidemiology, clinical features, pathogenesis, and interventions. We also highlight the environmental factors that are thought to play an important role in addition to genetics in the pathogenesis of LADA. In the future, high-throughput molecular profiles might shed light on the nature of LADA among the wide spectrum of diabetes and offer new opportunities to identify novel LADA-specific biomarkers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.330
Teacher spread0.297 · 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 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

Citations49
Published2019
Admission routes1
Has abstractyes

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