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Record W4409457089 · doi:10.3899/jrheum.2025-0274

Revisiting Magnetic Resonance Imaging Structural Lesions in the Sacroiliac Joints

2025· editorial· en· W4409457089 on OpenAlexaffvenue
Denis Poddubnyy

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typeeditorial
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsUniversity Health Network
FundersPfizerEli Lilly and Company
KeywordsMedicineMagnetic resonance imagingSacroiliac jointNuclear magnetic resonanceRadiology

Abstract

fetched live from OpenAlex

The study by Weber et al,1 investigating the effect of age on active and structural magnetic resonance imaging (MRI) lesions in the sacroiliac joints (SIJs) of healthy individuals and patients with nonspecific back pain (NSBP), provides important insights that refine our understanding of the diagnostic utility of MRI findings in axial spondyloarthritis (axSpA). MRI scans from healthy volunteers and patients with NSBP aged ≤ 45 years from 3 independent cohorts (MORPHO; Scientific Investigation of MRI and Biochemical Markers in Patients With Axial Spondyloarthritis, Back Pain of Other Reasons, Subjects With Strain in the Sacroiliac Joints and Healthy Subjects [MASH]; and Assessment of SpondyloArthritis international Society classification cohort [ASAS-CC]) were reviewed by 2-7 trained and calibrated readers per cohort.1

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)0.005
metaresearch head score (Gemma)0.013
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0020.003
Scholarly communication0.0050.003
Open science0.0030.001
Research integrity0.0150.014
Insufficient payload (model declined to judge)0.0030.003

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 head0.008
GPT teacher head0.287
Teacher spread0.279 · 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
GenreEditorial

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
Published2025
Admission routes2
Has abstractyes

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