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Record W2777883950

Het herkennen van patiënten met spondyloartritis. Nieuwe classificatiecriteria

2011· article· nl· W2777883950 on OpenAlexaff
Robert Landewé, Désirée van der Heijde

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2011
Typearticle
Languagenl
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineSacroiliitisAnkylosing spondylitisPsoriasisUveitisTumor necrosis factor alphaRadiographySpondylitisDiseaseHLA-B27Axial spondyloarthritisDermatologySurgeryPathologyHuman leukocyte antigenInternal medicineImmunologyAntigen
DOInot available

Abstract

fetched live from OpenAlex

Spondyloarthritis (SpA) is an umbrella term for a group of rheumatic diseases characterised by inflammation of the sacroiliac (SI) joints and vertebral column; today, differentiation is made between axial SpA and peripheral SpA. Ankylosing spondylitis (Bechterew's disease) is the most typical form of axial SpA whereby sacroiliitis can be found on X-rays of the SI joints. Axial SpA can, however, also be present without radiographic evidence of sacroiliitis. A range of SpA-related symptoms can also manifest themselves outside the musculoskeletal system, for example, uveitis, psoriasis and inflammatory intestinal diseases. Tumour necrosis factor (TNF)-α inhibitors play an important role in the treatment of SpA. New classification criteria have recently been established in which MRI of the SI joints and the presence of the HLA-B27 tissue antigen are key. Axial and peripheral SpA should be recognized early in order to be able to successfully treat these conditions

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.058
GPT teacher head0.269
Teacher spread0.211 · 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 designTheoretical or conceptual
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

Citations1
Published2011
Admission routes1
Has abstractyes

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