MétaCan
Menu
Back to cohort
Record W2913118491 · doi:10.3899/jrheum.181095

OMERACT Definitions for Ultrasonographic Pathologies and Elementary Lesions of Rheumatic Disorders 15 Years On

2019· article· en· W2913118491 on OpenAlexvenueno aff
George A W Bruyn, Annamaria Iagnocco, Esperanza Naredo, Péter Bálint, Marwin Gutiérrez, Hilde Berner Hammer, Paz Collado, Georgios Filippou, Wolfgang Schmidt, Sandrine Jousse‐Joulin, Péter Mandl, Philip G. Conaghan, Richard J. Wakefield, Helen Keen, Lene Terslev, Maria Antonietta D’Agostino

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersLeeds Biomedical Research CentreAgence Nationale de la RechercheNational Institute for Health and Care Research
KeywordsMedicineTerminologyRheumatologyPhysical therapyScoring systemMedical physicsClinical trialInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Ultrasound (US) Working Group (WG) operates research activities for the validation of US as an outcome measurement instrument according to the Filter 2.0 framework. METHODS: Original publications on definitions and scoring systems for pathophysiological manifestations and elementary lesions of various rheumatic disorders were reviewed from the onset of the WG research in 2005. RESULTS: Definitions and scoring systems according to new terminology are provided. CONCLUSION: We have redefined OMERACT US pathology and elementary lesions as well as scoring systems, which are now proposed for OMERACT approval for application in clinical trials.

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)0.008
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.004
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.281
Teacher spread0.258 · 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
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

Citations278
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of RheumatologySame topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207