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Record W3129560371 · doi:10.3899/jrheum.201676

Magnetic Resonance Imaging of Axial and Peripheral Disease in Psoriatic Arthritis: A Report From the 2020 GRAPPA Annual Meeting

2021· article· en· W3129560371 on OpenAlexaffvenue
Walter P. Maksymowych, Mikkel Østergaard

Bibliographic record

VenueThe Journal of Rheumatology · 2021
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsoriatic arthritisMedicineMagnetic resonance imagingPsoriasisEnthesisArthritisModality (human–computer interaction)RadiologyPathologyDermatologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Psoriatic arthritis (PsA) presents with diverse features of musculoskeletal inflammation that affect both axial and peripheral joints as well as entheses, tenosynovium, and bursae. Magnetic resonance imaging (MRI) is the imaging modality that is uniquely capable of identifying pathology in all these structures. The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) Magnetic Resonance Imaging Working Group has increasingly explored diverse MRI methodologies for the purposes of quantifying inflammatory and structural abnormalities in clinical trials and research. The 2020 GRAPPA virtual workshop presented an opportunity to review progress in the field, summarize the status of MRI scoring systems developed for PsA, and review representative patient cases.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.237
Teacher spread0.232 · 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 designObservational
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

Citations5
Published2021
Admission routes2
Has abstractyes

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