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Record W2325880029 · doi:10.3899/jrheum.110884

Dr. Rios Fernández, <i>et al,</i> reply

2011· article· en· W2325880029 on OpenAlexvenueno aff
Raquel Ríos-Fernández, José Luís Callejas-Rubio, Concepción Fernández Roldán, Norberto Ortego‐Centeno

Bibliographic record

VenueThe Journal of Rheumatology · 2011
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVitamin D and neurologyFernvitamin D deficiencyVitaminCalcitriol receptorInternal medicineEndocrinologyPhysiologyBiologyBotany

Abstract

fetched live from OpenAlex

To the Editor: Gambichler and colleagues1 have concluded that prevalence of vitamin D deficiency is high in patients with systemic sclerosis (SSc) and is probably not dependent on the patient’s geographic origin. In the past decade there has been renewed interest in vitamin D, with a proliferation of published studies on the effects of vitamin D in varying clinical conditions. Classically, vitamin D has been linked to mineral metabolism and its deficiency with bone disease, but interest in the nonskeletal effects has been increasing since the discovery of vitamin D receptors and the 1α-hydroxylase enzyme in multiple tissues. Vitamin … Address correspondence to Dr. Rios Fernández; E-mail: rriosfer{at}hotmail.com

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)0.016
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.017
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0170.020
Insufficient payload (model declined to judge)0.0060.004

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 head0.325
Teacher spread0.278 · 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
GenreCommentary

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
Published2011
Admission routes1
Has abstractyes

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