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Infection-Related Myelopathies

2021· review· en· W3206478584 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Pathology Mechanisms of Disease · 2021
Typereview
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity of Toronto
FundersEpilepsy SocietyNational Institutes of HealthOntario Institute for Regenerative MedicineYork UniversityHospital for Sick ChildrenMultiple Sclerosis SocietyBiogen
KeywordsMyelopathyMyelin oligodendrocyte glycoproteinMyelitisMedicineNeuromyelitis opticaAutoantibodyDemyelinating DisorderImmunologyTransverse myelitisOligodendrocyteMultiple sclerosisSpinal cordAntibodyPathologyVirologyMyelinCentral nervous systemExperimental autoimmune encephalomyelitisInternal medicine

Abstract

fetched live from OpenAlex

Recent years have seen growing attention to inflammatory and infectious disorders of the spinal cord, not only due to the discovery of autoantibody-mediated disorders of the spinal cord [e.g., aquaporin-4 immunoglobulin G (IgG) antibodies and myelin oligodendrocyte glycoprotein IgG antibodies], but also due to the emergence of clusters of infection-related myelopathy, now known as acute flaccid myelitis. We review the spectrum of infection-related myelopathies and outline a nosological classification system based on association with infection. We describe the epidemiology and definitions of myelopathies, with a discussion of clinical presentation and neuroimaging features, and then turn to specific discussion of myelopathies due to direct pathogen invasion and those considered to be post- or parainfectious.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.338
Teacher spread0.321 · 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