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Record W2002444618 · doi:10.1055/s-2007-1019124

The Immunology of Multiple Sclerosis

2008· review· en· W2002444618 on OpenAlexaff
Amit Bar‐Or

Bibliographic record

VenueSeminars in Neurology · 2008
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMultiple sclerosisImmune systemMedicineNeuroscienceDiseasePathophysiologyImmunologyInflammationCentral nervous systemBiologyPathology

Abstract

fetched live from OpenAlex

Recent years have witnessed a remarkable growth in literature related to the biology and treatment of multiple sclerosis (MS). The focus of this article is on aspects of the human immune response that have been implicated in the MS disease process and, as a corollary, represent rational targets for the development of safe and effective therapies. Much of the thinking about immune pathophysiology in patients with MS has been shaped by studies in animal models of central nervous system (CNS) inflammation. Translation to the human disease has continued to pose challenges. A simplified model of MS immune pathophysiology is presented to illustrate the basic principles by which peripheral immune activation, as well as compartmentalized immune responses within the CNS, is likely to impact the disease process and to identify the putative sites of action of current and future MS treatments.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.109
GPT teacher head0.352
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations158
Published2008
Admission routes1
Has abstractyes

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