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Record W2897077682 · doi:10.7759/cureus.3460

Depression and Catatonia: A Case of Neuropsychiatric Complications of Moyamoya Disease

2018· article· en· W2897077682 on OpenAlexaff
Jonathan Lai, Abdurraoof Patel, Charlotte Dandurand, Peter Gooderham, Shaohua Lu

Bibliographic record

VenueCureus · 2018
Typearticle
Languageen
FieldMedicine
TopicMoyamoya disease diagnosis and treatment
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsCatatoniaMoyamoya diseaseDepression (economics)MedicineDiseasePsychiatryPediatricsPopulationInternal medicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Moyamoya disease (MMD) is a rare idiopathic cerebrovascular disease most common among the Asian population. Studies have shown that patients with MMD are at increased risk for developing psychiatric complications. We present a patient with hemorrhagic MMD (RNF213 gene mutation) who developed depression and catatonia over time following MMD-related strokes. While no guidelines exist for the management of such an uncommon scenario, it at least requires an interdepartmental approach. Our report highlights the medical complications of untreated MMD and its neuropsychiatric association with depression and catatonia.

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)0.002
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.307
Teacher spread0.291 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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