MétaCan
Menu
Back to cohort
Record W2106275880 · doi:10.1192/bjp.bp.111.092197

Anti-NMDA receptor encephalitis: an important differential diagnosis in psychosis

2011· article· en· W2106275880 on OpenAlexaff
Helen Barry, Orla Hardiman, Daniel G. Healy, Mary T. Keogan, Joan T. Moroney, Péter Molnár, David Cotter, Kieran C. Murphy

Bibliographic record

VenueThe British Journal of Psychiatry · 2011
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsPsychosisEncephalitisAnti-NMDA receptor encephalitisNMDA receptorNeuroscienceDifferential diagnosisPsychologyMedicineReceptorVirologyPsychiatryPathologyInternal medicine

Abstract

fetched live from OpenAlex

We present four cases of confirmed anti-NMDA receptor encephalitis; three presented initially with serious psychiatric symptoms and the other developed significant psychiatric symptoms during the initial phase of illness. Brain biopsy findings of one patient are also described. Psychiatrists should consider anti-NMDA receptor encephalitis in patients presenting with psychosis and additional features of dyskinesias, seizures and catatonia, particularly where there is no previous history of psychiatric disorder.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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 designNot applicable
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

Citations112
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueThe British Journal of PsychiatrySame topicAutoimmune Neurological Disorders and TreatmentsFrench-language works237,207