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Record W2130265167 · doi:10.1136/pgmj.2010.101121

The cure of ageing: vitamin D—magic or myth?

2010· review· en· W2130265167 on OpenAlexaff
Michael P. Chu, Kannayiram Alagiakrishnan, Cheryl A Sadowski

Bibliographic record

VenuePostgraduate Medical Journal · 2010
Typereview
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineVitamin D and neurologyAgeingVitaminBioinformaticsvitamin D deficiencyImmune systemImmune modulationIntensive care medicineGerontologyPhysiologyImmunologyEndocrinologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Vitamin D was initially thought only to function in calcium homeostasis. However, it has multiple roles in human health, including neuromuscular and immune modulation. Recently, its deficiency is increasingly implicated in many diseases. This discovery has led both popular culture and research to find ways that vitamin D can either treat or prevent many diseases. Since vitamin D not only affects the expression of many genes, but also has intra-individual pharmacokinetic variation, a simplistic cause and effect between vitamin D deficiency and illnesses should not be expected. Older adults pose a challenge not only because diseases become more prevalent with ageing, but they also are often complicated with other comorbidities. This article reviews the link of vitamin D deficiency and the associated medical conditions in middle aged and older adults. It also examines the variability in testing vitamin D values and evaluates dosing recommendations based on current evidence.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.080
GPT teacher head0.422
Teacher spread0.342 · 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 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

Citations33
Published2010
Admission routes1
Has abstractyes

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