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Record W4205286920 · doi:10.1017/cjn.2021.506

Neurosarcoidosis-Induced Multiple Cerebral Microinfarcts

2022· article· en· W4205286920 on OpenAlexaffvenue
Charlotte Gallienne, Jian‐Qiang Lu, Devin Hall, Crystal Fong

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoidosis and Beryllium Toxicity Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNeurosarcoidosisContent (measure theory)SarcoidosisMedicineComputer scienceDermatologyMathematics

Abstract

fetched live from OpenAlex

A 58-year-old man with a history of coronary heart disease, ischemic cardiomyopathy, hypertension, and dyslipidemia presented with fatigue, left-sided headache, and mild confusion for 1 month.He was treated for presumed HSV encephalitis and improved after 3 weeks of acyclovir.Two days following discharge, he returned with new onset ataxia and multiple falls.He was continued on acyclovir, and broad-spectrum coverage via vancomycin and ceftriaxone was initiated for suspected bacterial meningitis, given his unusual presentation.Despite these medications, his cognitive symptoms, namely confusion, short-term memory impairment, and disorientation in time, space, and person, progressively worsened.He developed paranoid behaviors and visual hallucinations.Cerebrospinal fluid examination revealed elevated protein (57.13 g/L), leukocytes (66 × 10 6 /L), and glucose (5.2 mmol/L) with oligoclonal bands but was negative for malignant cells, HSV-1, HSV-2, VZV, enterovirus, fungi, cryptococcal antigen, acid-fast bacillus, and other bacteria.Electroencephalogram showed no seizure activity.Initial contrast-enhanced MRI head demonstrated nodular leptomeningeal enhancement of the right temporal convexity sulci (Figure 1A, arrows), nonspecific FLAIR signal abnormality Figure 1: MRI and right temporal biopsy pathology images.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.067
GPT teacher head0.305
Teacher spread0.237 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicSarcoidosis and Beryllium Toxicity ResearchFrench-language works237,207