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Record W3175960872 · doi:10.1017/cjn.2021.138

Discussing Challenges in Diagnosis of Tuberculous Meningitis and Neurosarcoidosis

2021· article· en· W3175960872 on OpenAlexvenueno aff
Alba Santos, Florian Desgranges, Marina Jovanović, Angelica Anichini, Antonios Kritikos, Vincent Dunet, Jean‐Philippe Brouland, Marie Théaudin, Caroline Pot, Renaud Du Pasquier, Vasiliki Pantazou

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2021
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeurosarcoidosisMeningitisTuberculous meningitisSarcoidosisIntensive care medicinePediatricsDermatology

Abstract

fetched live from OpenAlex

Isolated chronic granulomatous meningitis remains a diagnostic challenge for the physician. Symptoms are often nonspecific and ancillary tests have low-sensitivity rates, which may delay targeted treatment and lead to increased morbidity and mortality. Here, we discuss the challenges in diagnosing and treating patients with chronic meningitis by reporting two cases of previously healthy patients who presented with granulomatous meningitis on brain biopsy.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.279
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designObservational
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicInfectious Diseases and TuberculosisFrench-language works237,207