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Record W4296312389 · doi:10.1186/s12931-022-02147-x

Recent advances in vitamin D implications in chronic respiratory diseases

2022· review· en· W4296312389 on OpenAlexaff
Mellissa Gaudet, Maria Plesa, Andrea Mogas, Nour Jalaleddine, Qutayba Hamid, Saba Al Heialy

Bibliographic record

VenueRespiratory Research · 2022
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University Health Centre
FundersMohammed Bin Rashid University of Medicine and Health SciencesAl Jalila Foundation
KeywordsMedicineVitamin D and neurologyvitamin D deficiencyImmunologyIntensive care medicineContext (archaeology)Respiratory tract infectionsRespiratory diseaseDiseaseRespiratory systemInternal medicineLungBiology

Abstract

fetched live from OpenAlex

) deficiency has been shown to be highly prevalent in patients with chronic airway inflammatory and infectious diseases, correlated with increased disease severity. It has been established that vitamin D modulates ongoing abnormal immune responses in chronic respiratory diseases and is shown to restrict bacterial and viral colonization into the lungs. On the contrary, other studies revealed controversy findings regarding vitamin D efficacy in respiratory diseases. This review aims to update the current evidence regarding the role of vitamin D in airway inflammation and in various respiratory diseases. A comprehensive search of the last five years of literature was conducted using MEDLINE and non-MEDLINE PubMed databases, Ovid MEDLINE, SCOPUS-Elsevier, and data from in vitro and in vivo experiments, including clinical studies. This review highlights the importance of understanding the full range of implications that vitamin D may have on lung inflammation, infection, and disease severity in the context of chronic respiratory 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.

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)0.002
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.181
GPT teacher head0.476
Teacher spread0.295 · 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

Citations48
Published2022
Admission routes1
Has abstractyes

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