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Record W2342517290 · doi:10.14740/jem.v6i2.346

An Ultra-Elderly Case of Acute-Onset Autoimmune Type 1 Diabetes Mellitus

2016· article· en· W2342517290 on OpenAlexvenueno aff
Hiroshi Yamaguchi, Takafumi Kanadani, Masumi Ohno, Atsuhisa Shirakami

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusType 2 Diabetes MellitusKetosisPediatricsType 2 diabetesInternal medicineType 1 diabetesPopulationEndocrinology

Abstract

fetched live from OpenAlex

We herein described a 96-year-old woman who was referred to our hospital for a drowsy state. Since her blood glucose level was 600 mg/dL, HbA1c was 11.2%, and serum beta-ketone bodies were low, she was diagnosed with diabetic ketosis and hyperglycemic hyperosmolar state. Acute-onset type 1 diabetes mellitus was diagnosed based on the diagnostic criteria for acute-onset type 1 diabetes mellitus (2012) by the Committee of the Japan Diabetes Society. There are currently no epidemiological data available for the elderly with acute-onset type 1 diabetes in the Japanese population. This case revealed that acute type 1 diabetes may develop not only in the young-old or old-old, but also in the ultra-elderly. To the best of our knowledge, our case is the oldest among ultra-elderly cases of acute-onset type 1 diabetes mellitus. J Endocrinol Metab. 2016;6(2):71-74 doi: http://dx.doi.org/10.14740/jem346w

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.250
Teacher spread0.244 · 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 designCase report
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

Citations4
Published2016
Admission routes1
Has abstractyes

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