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Record W2402842547 · doi:10.1097/wno.0000000000000256

Vitamin D in Multiple Sclerosis and Central Nervous System Demyelinating Disease—A Review

2015· review· en· W2402842547 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.

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2015
Typereview
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultiple sclerosisDemyelinating diseaseMedicineDiseaseVitamin D and neurologyClinical trialNeuroprotectionCentral nervous systemImmune systemImmunologyNeurosciencePathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The role of vitamin D as both a risk factor and a disease modifier in multiple sclerosis (MS) has a storied history with ongoing accumulation of supportive convergent evidence from animal data, clinical studies and trials, and biomarkers of disease. EVIDENCE ACQUISITION: A detailed review of the published literature ranging from in vivo immune studies to human clinical studies of epidemiology, physiology, immunology, clinical, and radiological markers was undertaken. RESULTS: There is compelling evidence that vitamin D is not only a risk factor for central nervous system (CNS) demyelinating disease (namely MS) but also seems to modify both the inflammatory and neurodegenerative elements of the disease, with large-scale treatment trials underway. The authors also address questions of interest that remain unanswered. CONCLUSIONS: Vitamin D is an important contributor and modifiable risk factor in CNS demyelinating disease. Further work will determine whether it is also neuroprotective and if such benefits will apply to other inflammatory and degenerative neurological diseases.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.168
GPT teacher head0.383
Teacher spread0.215 · 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