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Record W2728051827 · doi:10.1093/geroni/igx004.3487

VITAMIN D DEFICIENCY IN GAIT AND COGNITION. LESSONS LEARNED FROM THE GAIT & BRAIN STUDY

2017· article· en· W2728051827 on OpenAlexaff
Manuel Montero‐Odasso

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsWestern University
Fundersnot available
KeywordsGaitVitamin D and neurologyCognitionvitamin D deficiencyMedicinePhysical medicine and rehabilitationNeuroprotectionCognitive declinePhysical therapyPsychologyInternal medicineDementiaPsychiatryDisease

Abstract

fetched live from OpenAlex

This talk will review recent provocative studies that have demonstrated relationships between Vitamin D deficiency with poor cognitive and mobility performance in older adults. Interventional studies supplementing vitamin D have shown mixed result concerning cognitive and mobility outcomes. Results from the GAIT & BRAIN Study and from a recent meta-analysis will be presented showing that Vitamin D supplementation in doses higher that the current recommendation of 800 IUd/d would be needed to achieve serum levels over 75nml/l which seems needed to improve cognitive and mobility outcomes in older adults with Vitamin D deficiency. Potential neuroprotective vitamin D attributes through antioxidative mechanisms, neuronal calcium regulation, immunomodulation, enhanced nerve conduction and detoxification mechanisms will be reviewed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.047
GPT teacher head0.328
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), 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
Published2017
Admission routes1
Has abstractyes

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