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Record W2910119826 · doi:10.14740/jem.v8i6.542

A Case of Mitochondrial Disease First Diagnosed Over 30 Years After Onset

2018· article· en· W2910119826 on OpenAlexvenueno aff
Ryo Watanabe, Hidekatsu Yanai, Haruka Kamata, Hiroko Yamazaki

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMitochondrial DNAMedicineAtrophyMitochondrial diseaseMagnetic resonance imagingFundus (uterus)PathologyDiseaseExtraocular musclesPtosisOphthalmologyInternal medicineGeneGeneticsRadiologyBiology

Abstract

fetched live from OpenAlex

Mitochondrial disease is induced by mutations in both mitochondrial DNA and DNA of nuclear genes that encode mitochondrial proteins, and there is a general lack of genotype-phenotype correlation in many mitochondrial disorders, which makes the diagnosis of mitochondrial disease difficult. We treated a 37-year-old woman with congenital cataract, bilateral sensory deafness, severe bilateral ptosis, oculomotor disorder in all directions and systemic muscular atrophy and weakness. These clinical characteristics made us perform further examinations, and we found ischemic change in brain and remarkable atrophy of extraocular muscles by magnetic resonance imaging (MRI), optic atrophy by fundus examination and high levels of serum lactate and lactate/pyruvate ratio, which confirmed the diagnosis of mitochondrial disease. Finally, she was diagnosed with having mitochondrial disease for over 30 years after onset. J Endocrinol Metab. 2018;8(6):149-152 doi: https://doi.org/10.14740/jem542

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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