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Record W3005491818 · doi:10.3899/jrheum.200129

GRAPPA 2019 Project Report

2020· article· en· W3005491818 on OpenAlexaffvenue
Niti Goel, Laura C. Coates, Gabriele De Marco, Lihi Eder, Oliver FitzGerald, Philip Helliwell, Ying Ying Leung, Walter P. Maksymowych, Philip J. Mease, Mikkel Østergaard, Denis O’Sullivan, Denis Poddubnyy, Christopher T. Ritchlin, Dafna D. Gladman

Bibliographic record

VenueThe Journal of Rheumatology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsUniversity of AlbertaWomen's College HospitalUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicineMEDLINEMedical physics

Abstract

fetched live from OpenAlex

At the 2019 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), members received updates on several ongoing efforts. Among them were updates on research, including the trainee symposium, pilot research grants, and the Collaborative Research Network; GRAPPA's patient research partners; education, including the slide collection; treatment recommendations; and additional work related to advancing the understanding of disease aspects, including the Outcome Measures in Rheumatology (OMERACT)-GRAPPA outcome measure, axial involvement, and ultrasound enthesitis projects; as well as the early psoriatic disease systematic literature review and magnetic resonance imaging.

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)0.016
metaresearch head score (Gemma)0.031
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: Other · Consensus signal: none
Teacher disagreement score0.261
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0060.002
Open science0.0030.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2610.171

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 head0.033
GPT teacher head0.238
Teacher spread0.205 · 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
GenreOther

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

Citations9
Published2020
Admission routes2
Has abstractyes

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