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Record W7099308191

Journal of Neurology, Neurosurgery, and Psychiatry 1986;49:113-123 The mystery of the origin of multiple sclerosis

2016· article· en· W7099308191 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisGliosisPathogenesisEtiologyDiseaseGenetic predispositionImmune system
DOInot available

Abstract

fetched live from OpenAlex

SUMMARY Our present understanding of the aetiology and pathogenesis of multiple sclerosis is discussed in relation to the views of Sir William Gowers. He perceived that both environmental and genetic factors might be implicated in the aetiology of the disease. Evidence for the former was first reported in 1903, but has become convincing only in the past 20 years; the nature of the environ-mental factor remains obscure. Evidence for a genetic influence on susceptibility has accumulated since the 1 930s, the most compelling coming from the recent Canadian twin study. The number and mode of operation of the genetic factors is still uncertain, but there is evidence for the implication of genetically controlled cellular immune mechanisms in the pathogenesis of the disease. The precise relationship between transient changes in immunological status and the development ofnew lesions has yet to be defined; magnetic resonance imaging (MRI) promises to play a significant role in this analysis because of its sensitivity in detecting abnormalities in multiple sclerosis. MRI is not in itself specific; it is probable that the similar appearances in multiple sclerosis and cerebral vascular disease both derive at least in part from the influence of astrocytic gliosis on proton content and distribution. The significance of the gliosis is uncertain. Gowers believed that the primary defect in multiple sclerosis lay in the astrocyte. Recent observations on the immunological functions of this cell in vitro

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.083

Codex and Gemma teacher scores by category

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

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 head0.061
GPT teacher head0.194
Teacher spread0.134 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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