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Record W2905107440 · doi:10.1155/2018/6359174

RNF213 Variant Diversity Predisposes Distinct Populations to Dissimilar Cerebrovascular Diseases

2018· review· en· W2905107440 on OpenAlexaboutno aff
Jing Lin, Wenli Sheng

Bibliographic record

VenueBioMed Research International · 2018
Typereview
Languageen
FieldMedicine
TopicMoyamoya disease diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMoyamoya diseasePopulationMedicineBiologyGeneticsInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

In recent years, the ring finger protein 213 gene (RNF213) has gradually attracted attention, mainly because it has been found that RNF213 c.14429 G>A is associated with moyamoya disease (MMD) in East Asian populations. Recent studies have revealed that RFN213 is not only associated with MMD but is also connected with intracranial major artery stenosis/occlusion (ICASO) and intracranial aneurysm (IA). However, only the relationship between RNF213 c.14429 G>A and ICASO has been confirmed, and whether RNF213 has other mutations related to ICASO remains unclear. RNF213 and IA are currently only confirmed to be correlated in French-Canadian Population and no correlation has been found in the Japanese population. This review summarizes the advances in the associations between RNF213 and different cerebrovascular diseases and highlights that variant diversity of RNF213 may predispose distinct populations to dissimilar cerebrovascular diseases.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
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 head0.315
GPT teacher head0.500
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2018
Admission routes1
Has abstractyes

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