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Consensus-driven conceptual development of a standardized whole body-MRI scoring system for assessment of disease activity in juvenile idiopathic arthritis: MRI in JIA OMERACT working group

2021· article· en· W3195106536 on OpenAlexaff
Jyoti Panwar, Mirkamal Tolend, Bernadette Redd, Hemalatha Srinivasalu, Robert A. Colbert, Jonathan Akikusa, Simone Appenzeller, John A. Carrino, Nele Herregods, Lennart Jans, Kerri Highmore, Thekla von Kalle, Eva Kirkhus, Dax G. Rumsey, Jacob L. Jaremko, Inarejos Emilio J. Clemente, Marion A. van Rossum, Jennifer Stimec, Shirley M. L. Tse, Marinka Twilt, Nikolay Tzaribachev, Iwona Sudoł‐Szopińska, Arthur B. Meyers, Andréa S. Doria

Bibliographic record

VenueSeminars in Arthritis and Rheumatism · 2021
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversity of TorontoSickKids FoundationStollery Children's HospitalHospital for Sick Children
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of Health
KeywordsMedicineDelphi methodDelphiScoring systemPhysical therapyArthritisMedical physicsRadiologySurgeryInternal medicineArtificial intelligence

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.130
metaresearch head score (Gemma)0.113
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: Methods · Consensus signal: Methods
Teacher disagreement score0.130
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1300.113
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.002
Science and technology studies0.0020.003
Scholarly communication0.0050.003
Open science0.0060.005
Research integrity0.0020.006
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 head0.021
GPT teacher head0.297
Teacher spread0.277 · 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
GenreMethods

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

Citations27
Published2021
Admission routes1
Has abstractno

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