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Record W2971390942 · doi:10.1002/jnr.24524

Exercise in multiple sclerosis and its models: Focus on the central nervous system outcomes

2019· review· en· W2971390942 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

VenueJournal of Neuroscience Research · 2019
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsHotchkiss Brain InstituteUniversity of CalgaryWestern University
FundersCanadian Institutes of Health Research
KeywordsRemyelinationAstrogliosisMultiple sclerosisCentral nervous systemMedicineNeuroprotectionNeurodegenerationNeuroscienceNeuroinflammationDiseaseSpinal cord injuryExperimental autoimmune encephalomyelitisSpinal cordImmunologyPsychologyMyelinPathology

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a central nervous system (CNS) disorder characterized by inflammation, demyelination, and neurodegeneration. Emerging research suggests that exercise has therapeutic benefits for MS patients but the clinical data have focused primarily on non-CNS outcomes. In this review, we discuss evidence in preclinical MS models that exercise influences oligodendrocyte proliferation and repopulation, remyelination, neuroinflammation, neuroprotection, axonal regeneration, and astrogliosis. Evidence for the therapeutic effects of exercise in MS is further supplemented by data from other CNS diseases, including Alzheimer's disease, Parkinson's disease, and spinal cord injury. These results motivate studies into the benefits that exercise confers within the CNS in MS.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.594
GPT teacher head0.456
Teacher spread0.138 · 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