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Demographic, clinical, and cognitive characteristics of T2DM patients and healthy control subjects.<sup>*</sup>

2015· dataset· en· W6922890613 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2015
Typedataset
Languageen
FieldSocial Sciences
TopicGerman Social Sciences and History
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMetabolic control analysisMontreal Cognitive AssessmentDiabetes mellitusCreatinineWhite matterMagnetic resonance imagingType 2 diabetesBody mass index

Abstract

fetched live from OpenAlex

<p>*Data are presented as the mean ± SD unless otherwise noted; ** <i>p</i><0.05.</p><p>T2DM, type 2 diabetes mellitus; BMI, body mass index; HbA1c, glycated hemoglobin; HOMA2-S%, homeostasis model assessment for insulin sensitivity; ABI, ankle-brachial index; UACR, urine albumin creatinine ratio; MMSE, Mini Mental State Exam; MoCA, Montreal Cognitive Assessment; CDT, clock drawing test; MRI, magnetic resonance imaging; SVD, small vessel disease; WMLs, white matter lesions (these were assessed in both hemispheres using the Wahlund age-related white matter changes scale <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108883#pone.0108883-Wahlund1" target="_blank">[40]</a>).</p><p>Demographic, clinical, and cognitive characteristics of T2DM patients and healthy control subjects.<sup><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108883#nt101" target="_blank">*</a></sup></p>

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.052
GPT teacher head0.337
Teacher spread0.285 · 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
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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